Ausgabe 4/2019
Special Topics Issue on AI, Deep Learning, and Machine Learning. Guest Editors: Paul Nagy and Ashish Sharma
Inhalt (16 Artikel)
10 Steps to Strategically Build and Implement your Enterprise Imaging System: HIMSS-SIIM Collaborative White Paper
Henri Primo, Matthew Bishop, Louis Lannum, Dawn Cram, Abe Nader, Roger Boodoo
Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm
Selen Bozkurt, Emel Alkim, Imon Banerjee, Daniel L. Rubin
Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning
Jackson M. Steinkamp, Charles Chambers, Darco Lalevic, Hanna M. Zafar, Tessa S. Cook
Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks
Paul H. Yi, Abigail Lin, Jinchi Wei, Alice C. Yu, Haris I. Sair, Ferdinand K. Hui, Gregory D. Hager, Susan C. Harvey
RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning
Kenneth A. Philbrick, Alexander D. Weston, Zeynettin Akkus, Timothy L. Kline, Panagiotis Korfiatis, Tomas Sakinis, Petro Kostandy, Arunnit Boonrod, Atefeh Zeinoddini, Naoki Takahashi, Bradley J. Erickson
Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges
Mohammad Hesam Hesamian, Wenjing Jia, Xiangjian He, Paul Kennedy
Eye Tracking for Deep Learning Segmentation Using Convolutional Neural Networks
J. N. Stember, H. Celik, E. Krupinski, P. D. Chang, S. Mutasa, B. J. Wood, A. Lignelli, G. Moonis, L. H. Schwartz, S. Jambawalikar, U. Bagci
Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network
Md Zahangir Alom, Chris Yakopcic, Mst. Shamima Nasrin, Tarek M. Taha, Vijayan K. Asari
Reduction of False-Positive Markings on Mammograms: a Retrospective Comparison Study Using an Artificial Intelligence-Based CAD
Ray Cody Mayo, Daniel Kent, Lauren Chang Sen, Megha Kapoor, Jessica W. T. Leung, Alyssa T. Watanabe
Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography
Alyssa T. Watanabe, Vivian Lim, Hoanh X. Vu, Richard Chim, Eric Weise, Jenna Liu, William G. Bradley, Christopher E. Comstock
The Classification of Renal Cancer in 3-Phase CT Images Using a Deep Learning Method
Seokmin Han, Sung Il Hwang, Hak Jong Lee
Lens Identification to Prevent Radiation-Induced Cataracts Using Convolutional Neural Networks
Ross Filice
Assessment of Critical Feeding Tube Malpositions on Radiographs Using Deep Learning
Varun Singh, Varun Danda, Richard Gorniak, Adam Flanders, Paras Lakhani
Effectiveness of Deep Learning Algorithms to Determine Laterality in Radiographs
Ross W. Filice, Shelby K. Frantz
Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning Model
Sehyo Yune, Hyunkwang Lee, Myeongchan Kim, Shahein H. Tajmir, Michael S. Gee, Synho Do
Ankle Fracture Detection Utilizing a Convolutional Neural Network Ensemble Implemented with a Small Sample, De Novo Training, and Multiview Incorporation
Gene Kitamura, Chul Y. Chung, Barry E. Moore II