Search NASA⌕ Search

SEARCH · Search NASA

Results for “lifelong learning”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Design principles for lifelong learning AI accelerators

Lifelong learning-an agent's ability to learn throughout its lifetime-is a hallmark of biological learning systems and a central challenge for artificial intelligence (AI). The development of lifelong learning algorithms could lead to a range of novel AI applications, but this will also require the development of appropriate hardware accelerators, particularly if the models are to be deployed on edge platforms, which have strict size, weight and power constraints. Here we explore the design of lifelong learning AI accelerators that are intended for deployment in untethered environments. We identify key desirable capabilities for lifelong learning accelerators and highlight metrics to evaluate such accelerators. We then discuss current edge AI accelerators and explore the future design of lifelong learning accelerators, considering the role that different emerging technologies could play. The Perspective explores the future design of lifelong learning artificial intelligence (AI) accelerators that are intended for deployment in untethered environments, identifying key desirable capabilities for such edge AI accelerators and guidance on metrics to evaluate them.

42 ENGINEERING↗

Biological underpinnings for lifelong learning machines

Biological organisms learn from interactions with their environment throughout their lifetime. For artificial systems to successfully act and adapt in the real world, it is desirable to similarly be able to learn on a continual basis. This challenge is known as lifelong learning, and remains to a large extent unsolved. In this Perspective article, we identify a set of key capabilities that artificial systems will need to achieve lifelong learning. We describe a number of biological mechanisms, both neuronal and non-neuronal, that help explain how organisms solve these challenges, and present examples of biologically inspired models and biologically plausible mechanisms that have been applied to artificial systems in the quest towards development of lifelong learning machines. We discuss opportunities to further our understanding and advance the state of the art in lifelong learning, aiming to bridge the gap between natural and artificial intelligence. It is an outstanding challenge to develop intelligent machines that can learn continually from interactions with their environment, throughout their lifetime. Kudithipudi et al. review neuronal and non-neuronal processes in organisms that address this challenge and discuss pathways to developing biologically inspired approaches for lifelong learning machines.

Kudithipudi, Dhireesha↗

Task-Based Neuromodulation Architecture for Lifelong Learning

The conventional supervised deep learning frameworks for image classification focus on finding the minimizer of an objective function. However, for a lifelong learning system, a network has to be able to dynamically learn new tasks from very few examples. In biological neural networks, it is observed that neuromodulation acts as a key factor in continual learning. In this work, we propose a dynamic learning system, ModNet, wherein a modulatory unit regulates the learning depending on the context and the internal state of the system. The modulatory unit, which consists of a group of neurons, exercises the use of neuromodulation and Hebbian plasticity mechanisms over a population of neurons instead of relying on backpropagation of error gradients. An efficient digital architecture with on-chip training and resource sharing is proposed to facilitate the efficacy of task-based processing.

brain-inspired↗

Generative memory for lifelong machine learning

Techniques are disclosed for training machine learning systems. An input device receives training data comprising pairs of training inputs and training labels. A generative memory assigns training inputs to each archetype task of a plurality of archetype tasks, each archetype task representative of a cluster of related tasks within a task space and assigns a skill to each archetype task. The generative memory generates, from each archetype task, auxiliary data comprising pairs of auxiliary inputs and auxiliary labels. A machine learning system trains a machine learning model to apply a skill assigned to an archetype task to training and auxiliary inputs assigned to the archetype task to obtain output labels corresponding to the training and auxiliary labels associated with the training and auxiliary inputs assigned to the archetype task to enable scalable learning to obtain labels for new tasks for which the machine learning model has not previously been trained.

Nadamuni Raghavan, Aswin↗

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗

SU-E-I-42: Normalized Embryo/fetus Doses for Fluoroscopically Guided Pacemaker Implantation Procedures Calculated Using a Monte Carlo Technique

Purpose: It is well known that pacemaker implantation is sometimes needed in pregnant patients with symptomatic bradycardia. To our knowledge, there is no reported experience regarding radiation doses to the unborn child resulting from fluoroscopy during pacemaker implantation. The purpose of the current study was to develop a method for estimating embryo/fetus dose from fluoroscopically guided pacemaker implantation procedures performed on pregnant patients during all trimesters of gestation. Methods: The Monte Carlo N-Particle (MCNP) radiation transport code was employed in this study. Three mathematical anthropomorphic phantoms representing the average pregnant patient at the first, second and third trimesters of gestation were generated using Bodybuilder software (White Rock science, White Rock, NM). The normalized embryo/fetus dose from the posteroanterior (PA), the 30° left-anterior oblique (LAO) and the 30° right-anterior oblique (RAO) projections were calculated for a wide range of kVp (50–120 kVp) and total filtration values (2.5–9.0 mm Al). Results: The results consist of radiation doses normalized to a) entrance skin dose (ESD) and b) dose area product (DAP) so that the dose to the unborn child from any fluoroscopic technique and x-ray device used can be calculated. ESD normalized doses ranged from 0.008 (PA, first trimester) to 2.519 μGy/mGy (RAO, third trimester). DAP normalized doses ranged from 0.051 (PA, first trimester) to 12.852 μGy/Gycm2 (RAO, third trimester). Conclusion: Embryo/fetus doses from fluoroscopically guided pacemaker implantation procedures performed on pregnant patients during all stages of gestation can be estimated using the method developed in this study. This study was supported by the Greek Ministry of Education and Religious Affairs, General Secretariat for Research and Technology, Operational Program ‘Education and Lifelong Learning’, ARISTIA (Research project: CONCERT)

60 APPLIED LIFE SCIENCES↗

MO-B-19A-01: MOC: A How-To Guide

Medical physicists who were certified in 2002 or later, as well as those who become certified in the future, are enrolled in Maintenance of Certification. Many physicists with life-time certificates have voluntarily enrolled in MOC, as have physicists who volunteer their time to participate in the ABR exam development and administration processes. MOC consists of four components: Part 1, Professional standing; Part 2, Lifelong learning and self-assessment; Part 3, Cognitive expertise; and Part 4, Practice quality improvement. These four components together evaluate six competencies: Medical knowledge, patient care and procedural skills, interpersonal and communication skills, professionalism, practice-based learning and improvement, and systems-based practice. Parts 1, 2, and 3 of MOC are fairly straightforward, although many participants have questions about the process for attesting to professional standing, the opportunities for obtaining self-assessed continuing education, and the timing of the cognitive exam. MOC participants also have questions about Part 4, Practice Quality Improvement. PQI projects are powerful tools for improving the quality and safety of the environments in which we practice medical physics. In the current version of MOC known as “Continuous Certification” a medical physicist must have completed a PQI project within the previous three years, at the time of the ABR's annual look-back each March. For the first “full” annual look-back in March 2016, diplomates will be given an additional year, so that a PQI project completed in 2012, 2013, 2014, or 2015 will fulfill this requirement. Each component of MOC will be addressed, and the specifics of interest to medical physicists will be discussed. Learning Objectives: Understand the four components and six competencies evaluated by MOC. Become familiar with the annual requirements of Continuous Certification. Learn about opportunities for Practice Quality Improvement projects. Understand refinements occurring in the MOC program.

60 APPLIED LIFE SCIENCES↗

SU-E-I-80: Quantification of Respiratory and Cardiac Motion Effect in SPECT Acquisitions Using Anthropomorphic Models: A Monte Carlo Simulation Study

Purpose: The purpose of the present study was to quantify, evaluate the impact of cardiac and respiratory motion on clinical nuclear imaging protocols. Common SPECT and scintigraphic scans are studied using Monte Carlo (MC) simulations, comparing the resulted images with and without motion. Methods: Realistic simulations were executed using the GATE toolkit and the XCAT anthropomorphic phantom as a reference model for human anatomy. Three different radiopharmaceuticals based on 99mTc were studied, namely 99mTc-MDP, 99mTc—N—DBODC and 99mTc—DTPA-aerosol for bone, myocardium and lung scanning respectively. The resolution of the phantom was set to 3.5 mm{sup 3}. The impact of the motion on spatial resolution was quantified using a sphere with 3.5 mm diameter and 10 separate time frames, in the ECAM modeled SPECT scanner. Finally, respiratory motion impact on resolution and imaging of lung lesions was investigated. The MLEM algorithm was used for data reconstruction, while the literature derived biodistributions of the pharmaceuticals were used as activity maps in the simulations. Results: FWHM was extracted for a static and a moving sphere which was ∼23 cm away from the entrance of the SPECT head. The difference in the FWHM was 20% between the two simulations. Profiles in thorax were compared in the case of bone scintigraphy, showing displacement and blurring of the bones when respiratory motion was inserted in the simulation. Large discrepancies were noticed in the case of myocardium imaging when cardiac motion was incorporated during the SPECT acquisition. Finally the borders of the lungs are blurred when respiratory motion is included resulting to a dislocation of ∼2.5 cm. Conclusion: As we move to individualized imaging and therapy procedures, quantitative and qualitative imaging is of high importance in nuclear diagnosis. MC simulations combined with anthropomorphic digital phantoms can provide an accurate tool for applications like motion correction techniques’ optimization. This research has been co-funded by the European Union (European Social Fund) and Greek national resources under the framework of the ‘Archimedes III: Funding of Research Groups in TEI of Athens’ project of the ‘Education & Lifelong Learning’ Operational Programme.

60 APPLIED LIFE SCIENCES↗

SU-E-T-580: On the Significance of Model Based Dosimetry for Breast and Head and Neck 192Ir HDR Brachytherapy

Purpose: To assess the dosimetric and radiobiological differences between TG43-based and model-based dosimetry in the treatment planning of {sup 192}Ir HDR brachytherapy for breast and head and neck cancer. Methods: Two cohorts of 57 Accelerated Partial Breast Irradiation (APBI) and 22 head and neck (H&N) patients with oral cavity carcinoma were studied. Dosimetry for the treatment plans was performed using the TG43 algorithm of the Oncentra Brachy v4.4 treatment planning system (TPS). Corresponding Monte Carlo (MC) simulations were performed using MCNP6 with input files automatically prepared by the BrachyGuide software tool from DICOM RT plan data. TG43 and MC data were compared in terms of % dose differences, Dose Volume Histograms (DVHs) and related indices of clinical interest for the Planning Target Volume (PTV) and the Organs-At-Risk (OARs). A radiobiological analysis was also performed using the Equivalent Uniform Dose (EUD), mean survival fraction (S) and Tumor Control Probability (TCP) for the PTV, and the Normal Tissue Control Probability (N TCP) and the generalized EUD (gEUD) for the OARs. Significance testing of the observed differences performed using the Wilcoxon paired sample test. Results: Differences between TG43 and MC DVH indices, associated with the increased corresponding local % dose differences observed, were statistically significant. This is mainly attributed to their consistency however, since TG43 agrees closely with MC for the majority of DVH and radiobiological parameters in both patient cohorts. Differences varied considerably among patients only for the ipsilateral lung and ribs in the APBI cohort, with a strong correlation to target location. Conclusion: While the consistency and magnitude of differences in the majority of clinically relevant DVH indices imply that no change is needed in the treatment planning practice, individualized dosimetry improves accuracy and addresses instances of inter-patient variability observed. Research co-financed by the ESF and Greek funds through the Operational Program Education and Lifelong Learning Investing in Knowledge Society of the NSRF. Research Funding Program Aristeia. Nucletron, an Elekta company (Veenendaal, The Netherlands) is gratefully acknowledged for providing Oncentra Brachy v4.4 for research purposes.

61 RADIATION PROTECTION AND DOSIMETRY↗

SU-F-BRA-11: An Experimental Commissioning Test of Brachytherapy MBDCA Dosimetry, Based On a Commercial Radiochromic Gel/optical CT System

Purpose: To implement a 3D dose verification procedure of Model-Based Dose Calculation Algorithms (MBDCAs) for {sup 192}Ir HDR brachytherapy, based on a novel Ferrous Xylenol-orange gel (FXG) and optical CT read-out. Methods: The TruView gel was employed for absolute dosimetry in conjunction with cone-beam optical CT read-out with the VISTA scanner (both from Modus Medical Inc, London, ON, Canada). A multi-catheter skin flap was attached to a cylindrical PETE jar (d=9.6cm, h=16cm) filled with FXG, which served as both the dosimeter and the water equivalent phantom of bounded dimensions. X- ray CT image series of the jar with flap attached was imported to Oncentra Brachy v.4.5. A treatment plan consisting of 8 catheters and 56 dwell positions was generated, and Oncentra-ACE MBDCA as well as TG43 dose results were exported for further evaluation. The irradiation was carried out with a microSelecton v2 source. The FXG dose-response, measured via an electron irradiation of a second dosimeter from the same batch, was linear (R2>0.999) at least up to 12Gy. A MCNP6 input file was prepared from the DICOM-RT plan data using BrachyGuide to facilitate Monte Carlo (MC) simulation dosimetry in the actual experimental geometry. Agreement between experimental (reference) and calculated dose distributions was evaluated using the 3D gamma index (GI) method with criteria (5%-2mm applied locally) determined from uncertainty analysis. Results: The TG-43 GI failed, as expected, in the majority of voxels away from the flap (pass rate 59% for D>0.8Gy, corresponding to 10% of prescribed dose). ACE performed significantly better (corresponding pass rate 92%). The GI evaluation for the MC data (corresponding pass rate 97%) failed mainly at low dose points of increased uncertainty. Conclusion: FXG gel/optical CT is an efficient method for level-2 commissioning of brachytherapy MBDCAs. Target dosimetry is not affected from uncertainty introduced by TG43 assumptions in 192Ir skin brachytherapy. Research co-financed by the ESF and Greek funds through the Operational Program Education and Lifelong Learning Investing in Knowledge Society of the NSRF. Research Funding Program: Aristeia. Modus Medical Devices Inc. provided a TruView dosimeter batch and Nucletron, and Elekta company, provided access to Oncentra Brachy v4.5, for research purposes.

60 APPLIED LIFE SCIENCES↗

SU-F-BRA-12: End-User Oriented Tools and Procedures for Testing Brachytherapy TPSs Employing MBDCAs

Purpose: To develop user-oriented tools for commissioning and dosimetry testing of {sup 192}Ir brachytherapy treatment planning systems (TPSs) employing model based dose calculation algorithms (MBDCAs). Methods: A software tool (BrachyGuide) has been developed for the automatic generation of MCNP6 input files from any CT based plan exported in DICOM RT format from Elekta and Varian TPSs. BrachyGuide also facilitates the evaluation of imported Monte Carlo (MC) and TPS dose distributions in terms of % dose differences and gamma index (CT overlaid colormaps or relative frequency plots) as well as DVHs and related indices. For users not equipped to perform MC, a set of computational models was prepared in DICOM format, accompanied by treatment plans and corresponding MCNP6 generated reference data. BrachyGuide can then be used to compare institutional and reference data as per TG186. The model set includes a water sphere with the MBDCA WG {sup 192}Ir source placed centrically and in two eccentric positions, a water sphere with cubic bone and lung inhomogeneities and a five source dwells plan, and a patient equivalent model with an Accelerated Partial Breast Irradiation (APBI) plan. Results: The tools developed were used for the dosimetry testing of the Acuros and ACE MBDCAs implemented in BrachyVision v.13 and Oncentra Brachy v.4.5, respectively. Findings were consistent with previous results in the literature. Besides points close to the source dwells, Acuros was found to agree within type A uncertainties with the reference MC results. Differences greater than MC type A uncertainty were observed for ACE at distances >5cm from the source dwells and in bone. Conclusion: The tools developed are efficient for brachytherapy MBDCA planning commissioning and testing. Since they are appropriate for distribution over the web, they will be put at the AAPM WG MBDCA’s disposal. Research co-financed by the ESF and Greek funds. NSRF operational Program: Education and Lifelong Learning Investing in Knowledge Society-Aristeia. Varian Medical Systems and Nucletron, an Elekta company provided access to TPSs for research purposes. Miss Peppa was supported by IKY-fellowships of excellence for postgraduate studies in Greece,Siemens Program.

60 APPLIED LIFE SCIENCES↗

MO-F-CAMPUS-I-02: Occupational Conceptus Doses From Fluoroscopically-Guided Interventional Procedures

Purpose: The aim of this method was to provide dosimetric data on conceptus dose for the pregnant employee who participates in fluoroscopically-guided interventional procedures. Methods: Scattered air-kerma dose rates were obtained for 17 fluoroscopic projections involved in interventional procedures. These projections were simulated on an anthropomorphic phantom placed on the examination table supine. The operating theater was divided into two grids relative to the long table sides. Each grid consisted of 33 cells spaced 0.50 m apart. During the simulated exposures, at each cell, scatter air-kerma rate was measured at 110 cm from the floor i.e. at the height of the waist of the pregnant worker. Air-kerma rates were divided by the dose area product (DAP) rate of each exposure to obtain normalized data. For each projection, measurements were performed for 3 kVp and 3 filtration values i.e. for 9 different x-ray spectra. All measurements were performed by using a modern C-arm angiographic system (Siemens Axiom Artis, Siemens, Germany) and a radiation meter equipped with an ionization chamber. Results: The results consist of 153 iso-dose maps, which show the spatial distribution of DAP-normalized scattered air-kerma doses at the waist level of a pregnant worker. Conceptus dose estimation is possible using air-kerma to embryo/fetal dose conversion coefficients published in a previous study (J Cardiovasc Electrophysiol, Vol. 16, pp. 1–8, July 2005). Using these maps, occupationally exposed pregnant personnel may select a working position for a certain projection that keeps abdominal dose as low as reasonably achievable. Taking into consideration the regulatory conceptus dose limit for occupational exposure, determination of the maximum workload allowed for the pregnant personnel is also possible. Conclusion: Data produced in this work allow for the anticipation of conceptus dose and the determination of the maximum workload for a pregnant worker from any fluoroscopically-guided interventional procedure. This study was supported by the Greek Ministry of Education and Religious Affairs, General Secretariat for Research and Technology, Operational Program ‘Education and Lifelong Learning’, ARISTIA (Research project: CONCERT)

60 APPLIED LIFE SCIENCES↗

Summer High School Apprenticeship Research Program (SHARP)

The summer of 1997 will not only be noted by NASA for the mission to Mars by the Pathfinder but also for the 179 brilliant apprentices that participated in the SHARP Program. Apprentice participation increased 17% over last year's total of 153 participants. As indicated by the End-of-the-Program Evaluations, 96% of the programs' participants rated the summer experience from very good to excellent. The SHARP Management Team began the year by meeting in Cocoa Beach, Florida for the annual SHARP Planning Conference. Participants strengthened their Education Division Computer Aided Tracking System (EDCATS) skills, toured the world-renowned Kennedy Space Center, and took a journey into space during the Alien Encounter Exercise. The participants returned to their Centers with the same goals and objectives in mind. The 1997 SHARP Program goals were: (1) Utilize NASA's mission, unique facilities and specialized workforce to provide exposure, education, and enrichment experiences to expand participants' career horizons and inspire excellence in formal education and lifelong learning. (2) Develop and implement innovative education reform initiatives which support NASA's Education Strategic Plan and national education goals. (3) Utilize established statistical indicators to measure the effectiveness of SHARP's program goals. (4) Explore new recruiting methods which target the student population for which SHARP was specifically designed. (5) Increase the number of participants in the program. All of the SHARP Coordinators reported that the goals and objectives for the overall program as well as their individual program goals were achieved. Some of the goals and objectives for the Centers were: (1) To increase the students' awareness of science, mathematics, engineering, and computer technology; (2) To provide students with the opportunity to broaden their career objectives; and (3) To expose students to a variety of enrichment activities. Most of the Center goals and objectives were consistent with the overall program goals. Modem Technology Systems, Inc., was able to meet the SHARP Apprentices, Coordinators and Mentors during their site visits to Stennis Space Center, Ames Research Center and Dryden Flight Research Center. All three Centers had very efficient programs and adhered to SHARP's general guidelines and procedures. MTSI was able to meet the apprentices from the other Centers via satellite in July during the SHARP Video-Teleconference(ViTS). The ViTS offered the apprentices and the NASA and SHARP Coordinators the opportunity to introduce themselves. The apprentices from each Center presented topical "Cutting Edge Projects". Some of the accomplishments for the 1997 SHARP Program year included: MTSI hiring apprentices from four of the nine NASA Centers, the full utilization of the EDCATS by apprentices and NASA/SHARP Coordinators, the distribution of the SHARP Apprentice College and Scholarship Directory, a reunion with former apprentices from Langley Research Center and the development of a SHARP Recruitment Poster. MTSI developed another exciting newsletter containing graphics and articles submitted by the apprentices and the SHARP Management Team.

Source record↗

TH-E-201-00: Teaching Radiology Residents: What, How, and Expectation

The ABR Core Examination stresses integrating physics into real-world clinical practice and, accordingly, has shifted its focus from passive recall of facts to active application of physics principles. Physics education of radiology residents poses a challenge. The traditional method of didactic lectures alone is insufficient, yet it is difficult to incorporate physics teaching consistently into clinical rotations due to time constraints. Faced with this challenge, diagnostic medical physicists who teach radiology residents, have been thinking about how to adapt their teaching to the new paradigm, what to teach and meet expectation of the radiology resident and the radiology residency program. The proposed lecture attempts to discuss above questions. Newly developed diagnostic radiology residents physics curriculum by the AAPM Imaging Physics Curricula Subcommittee will be reviewed. Initial experience on hands-on physics teaching will be discussed. Radiology resident who will have taken the BAR Core Examination will share the expectation of physics teaching from a resident perspective. The lecture will help develop robust educational approaches to prepare radiology residents for safer and more effective lifelong practice. Learning Objectives: Learn updated physics requirements for radiology residents Pursue effective approaches to teach physics to radiology residents Learn expectation of physics teaching from resident perspective J. Zhang, This topic is partially supported by RSNA Education Scholar Grant.

61 RADIATION PROTECTION AND DOSIMETRY↗

TH-E-201-01: Diagnostic Radiology Residents Physics Curriculum and Updates

The ABR Core Examination stresses integrating physics into real-world clinical practice and, accordingly, has shifted its focus from passive recall of facts to active application of physics principles. Physics education of radiology residents poses a challenge. The traditional method of didactic lectures alone is insufficient, yet it is difficult to incorporate physics teaching consistently into clinical rotations due to time constraints. Faced with this challenge, diagnostic medical physicists who teach radiology residents, have been thinking about how to adapt their teaching to the new paradigm, what to teach and meet expectation of the radiology resident and the radiology residency program. The proposed lecture attempts to discuss above questions. Newly developed diagnostic radiology residents physics curriculum by the AAPM Imaging Physics Curricula Subcommittee will be reviewed. Initial experience on hands-on physics teaching will be discussed. Radiology resident who will have taken the BAR Core Examination will share the expectation of physics teaching from a resident perspective. The lecture will help develop robust educational approaches to prepare radiology residents for safer and more effective lifelong practice. Learning Objectives: Learn updated physics requirements for radiology residents Pursue effective approaches to teach physics to radiology residents Learn expectation of physics teaching from resident perspective J. Zhang, This topic is partially supported by RSNA Education Scholar Grant.

61 RADIATION PROTECTION AND DOSIMETRY↗

TH-E-201-02: Hands-On Physics Teaching of Residents in Diagnostic Radiology

The ABR Core Examination stresses integrating physics into real-world clinical practice and, accordingly, has shifted its focus from passive recall of facts to active application of physics principles. Physics education of radiology residents poses a challenge. The traditional method of didactic lectures alone is insufficient, yet it is difficult to incorporate physics teaching consistently into clinical rotations due to time constraints. Faced with this challenge, diagnostic medical physicists who teach radiology residents, have been thinking about how to adapt their teaching to the new paradigm, what to teach and meet expectation of the radiology resident and the radiology residency program. The proposed lecture attempts to discuss above questions. Newly developed diagnostic radiology residents physics curriculum by the AAPM Imaging Physics Curricula Subcommittee will be reviewed. Initial experience on hands-on physics teaching will be discussed. Radiology resident who will have taken the BAR Core Examination will share the expectation of physics teaching from a resident perspective. The lecture will help develop robust educational approaches to prepare radiology residents for safer and more effective lifelong practice. Learning Objectives: Learn updated physics requirements for radiology residents Pursue effective approaches to teach physics to radiology residents Learn expectation of physics teaching from resident perspective J. Zhang, This topic is partially supported by RSNA Education Scholar Grant.

61 RADIATION PROTECTION AND DOSIMETRY↗