Literature DB >> 31972556

An introduction to deep learning in medical physics: advantages, potential, and challenges.

Chenyang Shen1, Dan Nguyen, Zhiguo Zhou, Steve B Jiang, Bin Dong, Xun Jia.   

Abstract

As one of the most popular approaches in artificial intelligence, deep learning (DL) has attracted a lot of attention in the medical physics field over the past few years. The goals of this topical review article are twofold. First, we will provide an overview of the method to medical physics researchers interested in DL to help them start the endeavor. Second, we will give in-depth discussions on the DL technology to make researchers aware of its potential challenges and possible solutions. As such, we divide the article into two major parts. The first part introduces general concepts and principles of DL and summarizes major research resources, such as computational tools and databases. The second part discusses challenges faced by DL, present available methods to mitigate some of these challenges, as well as our recommendations.

Entities:  

Mesh:

Year:  2020        PMID: 31972556      PMCID: PMC7101509          DOI: 10.1088/1361-6560/ab6f51

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  78 in total

1.  Artificial Intelligence in Radiation Oncology Imaging.

Authors:  Reid F Thompson; Gilmer Valdes; Clifton David Fuller; Colin M Carpenter; Olivier Morin; Sanjay Aneja; William D Lindsay; Hugo J W L Aerts; Barbara Agrimson; Curtiland Deville; Seth A Rosenthal; James B Yu; Charles R Thomas
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-10-18       Impact factor: 7.038

2.  Adversarial attacks on medical machine learning.

Authors:  Samuel G Finlayson; John D Bowers; Joichi Ito; Jonathan L Zittrain; Andrew L Beam; Isaac S Kohane
Journal:  Science       Date:  2019-03-22       Impact factor: 47.728

3.  Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.

Authors:  Michiel Kallenberg; Kersten Petersen; Mads Nielsen; Andrew Y Ng; Christian Igel; Celine M Vachon; Katharina Holland; Rikke Rass Winkel; Nico Karssemeijer; Martin Lillholm
Journal:  IEEE Trans Med Imaging       Date:  2016-02-18       Impact factor: 10.048

4.  Intelligent Parameter Tuning in Optimization-Based Iterative CT Reconstruction via Deep Reinforcement Learning.

Authors:  Chenyang Shen; Yesenia Gonzalez; Liyuan Chen; Steve B Jiang; Xun Jia
Journal:  IEEE Trans Med Imaging       Date:  2018-06       Impact factor: 10.048

5.  Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching.

Authors:  Yanrong Guo; Yaozong Gao; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2015-12-11       Impact factor: 10.048

6.  MRI-only brain radiotherapy: Assessing the dosimetric accuracy of synthetic CT images generated using a deep learning approach.

Authors:  Samaneh Kazemifar; Sarah McGuire; Robert Timmerman; Zabi Wardak; Dan Nguyen; Yang Park; Steve Jiang; Amir Owrangi
Journal:  Radiother Oncol       Date:  2019-04-11       Impact factor: 6.280

7.  SEMI-SUPERVISED LEARNING FOR PELVIC MR IMAGE SEGMENTATION BASED ON MULTI-TASK RESIDUAL FULLY CONVOLUTIONAL NETWORKS.

Authors:  Zishun Feng; Dong Nie; Li Wang; Dinggang Shen
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2018-05-24

8.  Operating a treatment planning system using a deep-reinforcement learning-based virtual treatment planner for prostate cancer intensity-modulated radiation therapy treatment planning.

Authors:  Chenyang Shen; Dan Nguyen; Liyuan Chen; Yesenia Gonzalez; Rafe McBeth; Nan Qin; Steve B Jiang; Xun Jia
Journal:  Med Phys       Date:  2020-03-28       Impact factor: 4.071

9.  Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.

Authors:  Geert Litjens; Clara I Sánchez; Nadya Timofeeva; Meyke Hermsen; Iris Nagtegaal; Iringo Kovacs; Christina Hulsbergen-van de Kaa; Peter Bult; Bram van Ginneken; Jeroen van der Laak
Journal:  Sci Rep       Date:  2016-05-23       Impact factor: 4.379

10.  A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

Authors:  Dan Nguyen; Troy Long; Xun Jia; Weiguo Lu; Xuejun Gu; Zohaib Iqbal; Steve Jiang
Journal:  Sci Rep       Date:  2019-01-31       Impact factor: 4.379

View more
  20 in total

1.  Improving dose calculation accuracy in preclinical radiation experiments using multi-energy element resolved cone-beam CT.

Authors:  Yanqi Huang; Xiaoyu Hu; Yuncheng Zhong; Youfang Lai; Chenyang Shen; Xun Jia
Journal:  Phys Med Biol       Date:  2021-12-06       Impact factor: 3.609

2.  Improving robustness of a deep learning-based lung-nodule classification model of CT images with respect to image noise.

Authors:  Yin Gao; Jennifer Xiong; Chenyang Shen; Xun Jia
Journal:  Phys Med Biol       Date:  2021-12-07       Impact factor: 3.609

3.  On the robustness of deep learning-based lung-nodule classification for CT images with respect to image noise.

Authors:  Chenyang Shen; Min-Yu Tsai; Liyuan Chen; Shulong Li; Dan Nguyen; Jing Wang; Steve B Jiang; Xun Jia
Journal:  Phys Med Biol       Date:  2020-12-22       Impact factor: 3.609

Review 4.  Artificial intelligence and machine learning for medical imaging: A technology review.

Authors:  Ana Barragán-Montero; Umair Javaid; Gilmer Valdés; Dan Nguyen; Paul Desbordes; Benoit Macq; Siri Willems; Liesbeth Vandewinckele; Mats Holmström; Fredrik Löfman; Steven Michiels; Kevin Souris; Edmond Sterpin; John A Lee
Journal:  Phys Med       Date:  2021-05-09       Impact factor: 2.685

5.  Improving efficiency of training a virtual treatment planner network via knowledge-guided deep reinforcement learning for intelligent automatic treatment planning of radiotherapy.

Authors:  Chenyang Shen; Liyuan Chen; Yesenia Gonzalez; Xun Jia
Journal:  Med Phys       Date:  2021-02-16       Impact factor: 4.071

6.  Design and experimental validation of a unilateral magnet for MRI-guided small animal radiation experiments.

Authors:  Jace Grandinetti; Yuncheng Zhong; Chenyang Shen; Xun Jia
Journal:  J Magn Reson       Date:  2021-09-16       Impact factor: 2.229

7.  A hierarchical deep reinforcement learning framework for intelligent automatic treatment planning of prostate cancer intensity modulated radiation therapy.

Authors:  Chenyang Shen; Liyuan Chen; Xun Jia
Journal:  Phys Med Biol       Date:  2021-06-23       Impact factor: 3.609

8.  Semi-automatic sigmoid colon segmentation in CT for radiation therapy treatment planning via an iterative 2.5-D deep learning approach.

Authors:  Yesenia Gonzalez; Chenyang Shen; Hyunuk Jung; Dan Nguyen; Steve B Jiang; Kevin Albuquerque; Xun Jia
Journal:  Med Image Anal       Date:  2020-12-16       Impact factor: 8.545

9.  Experimental and numerical studies on kV scattered x-ray imaging for real-time image guidance in radiation therapy.

Authors:  Yanqi Huang; Kai Yang; Youfang Lai; Huan Liu; Chenyang Shen; Yuncheng Zhong; Yiping Shao; Xinhua Li; Bob Liu; Xun Jia
Journal:  Phys Med Biol       Date:  2021-02-11       Impact factor: 3.609

10.  Perspective on fast-evolving photoacoustic tomography.

Authors:  Junjie Yao; Lihong V Wang
Journal:  J Biomed Opt       Date:  2021-06       Impact factor: 3.170

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.