Artificial Intelligence in Radiation Therapy: First International Workshop, AIRT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

✍ Scribed by Dan Nguyen, Lei Xing, Steve Jiang

• Publisher: Springer International Publishing
• Year: 2019
• Tongue: English
• Leaves: 182
• Series: Lecture Notes in Computer Science 11850
• Edition: 1st ed. 2019
• Category: Library

✦ Synopsis

This book constitutes the refereed proceedings of the First International Workshop on Connectomics in Artificial Intelligence in Radiation Therapy, AIRT 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019.

The 20 full papers presented were carefully reviewed and selected from 24 submissions. The papers discuss the state of radiation therapy, the state of AI and related technologies, and hope to find a pathway to revolutionizing the field to ultimately improve cancer patient outcome and quality of life.

✦ Table of Contents

Front Matter ....Pages i-xi
Using Supervised Learning and Guided Monte Carlo Tree Search for Beam Orientation Optimization in Radiation Therapy (Azar Sadeghnejad Barkousaraie, Olalekan Ogunmolu, Steve Jiang, Dan Nguyen)....Pages 1-9
Feasibility of CT-Only 3D Dose Prediction for VMAT Prostate Plans Using Deep Learning (Siri Willems, Wouter Crijns, Edmond Sterpin, Karin Haustermans, Frederik Maes)....Pages 10-17
Automatically Tracking and Detecting Significant Nodal Mass Shrinkage During Head-and-Neck Radiation Treatment Using Image Saliency (Yu-chi Hu, Cynthia Polvorosa, Chiaojung Jillian Tsai, Margie Hunt)....Pages 18-25
4D-CT Deformable Image Registration Using an Unsupervised Deep Convolutional Neural Network (Yang Lei, Yabo Fu, Joseph Harms, Tonghe Wang, Walter J. Curran, Tian Liu et al.)....Pages 26-33
Toward Markerless Image-Guided Radiotherapy Using Deep Learning for Prostate Cancer (Wei Zhao, Bin Han, Yong Yang, Mark Buyyounouski, Steven L. Hancock, Hilary Bagshaw et al.)....Pages 34-42
A Two-Stage Approach for Automated Prostate Lesion Detection and Classification with Mask R-CNN and Weakly Supervised Deep Neural Network (Zhiyu Liu, Wenhao Jiang, Kit-Hang Lee, Yat-Long Lo, Yui-Lun Ng, Qi Dou et al.)....Pages 43-51
A Novel Deep Learning Framework for Standardizing the Label of OARs in CT (Qiming Yang, Hongyang Chao, Dan Nguyen, Steve Jiang)....Pages 52-60
Multimodal Volume-Aware Detection and Segmentation for Brain Metastases Radiosurgery (Szu-Yeu Hu, Wei-Hung Weng, Shao-Lun Lu, Yueh-Hung Cheng, Furen Xiao, Feng-Ming Hsu et al.)....Pages 61-69
Voxel-Level Radiotherapy Dose Prediction Using Densely Connected Network with Dilated Convolutions (Jingjing Zhang, Shuolin Liu, Teng Li, Ronghu Mao, Chi Du, Jianfei Liu)....Pages 70-77
Online Target Volume Estimation and Prediction from an Interlaced Slice Acquisition - A Manifold Embedding and Learning Approach (John Ginn, James Lamb, Dan Ruan)....Pages 78-85
One-Dimensional Convolutional Network for Dosimetry Evaluation at Organs-at-Risk in Esophageal Radiation Treatment Planning (Dashan Jiang, Teng Li, Ronghu Mao, Chi Du, Yongbin Liu, Shuolin Liu et al.)....Pages 86-93
Unpaired Synthetic Image Generation in Radiology Using GANs (Denis Prokopenko, Joël Valentin Stadelmann, Heinrich Schulz, Steffen Renisch, Dmitry V. Dylov)....Pages 94-101
Deriving Lung Perfusion Directly from CT Image Using Deep Convolutional Neural Network: A Preliminary Study (Ge Ren, Wai Yin Ho, Jing Qin, Jing Cai)....Pages 102-109
Individualized 3D Dose Distribution Prediction Using Deep Learning (Jianhui Ma, Ti Bai, Dan Nguyen, Michael Folkerts, Xun Jia, Weiguo Lu et al.)....Pages 110-118
Deep Generative Model-Driven Multimodal Prostate Segmentation in Radiotherapy (Kibrom Berihu Girum, Gilles Créhange, Raabid Hussain, Paul Michael Walker, Alain Lalande)....Pages 119-127
Dose Distribution Prediction for Optimal Treamtment of Modern External Beam Radiation Therapy for Nasopharyngeal Carcinoma (Bilel Daoud, Ken’ichi Morooka, Shoko Miyauchi, Ryo Kurazume, Wafa Mnejja, Leila Farhat et al.)....Pages 128-136
DeepMCDose: A Deep Learning Method for Efficient Monte Carlo Beamlet Dose Calculation by Predictive Denoising in MR-Guided Radiotherapy (Ryan Neph, Yangsibo Huang, Youming Yang, Ke Sheng)....Pages 137-145
UC-GAN for MR to CT Image Synthesis (Haitao Wu, Xiling Jiang, Fucang Jia)....Pages 146-153
CBCT-Based Synthetic MRI Generation for CBCT-Guided Adaptive Radiotherapy (Yang Lei, Tonghe Wang, Joseph Harms, Yabo Fu, Xue Dong, Walter J. Curran et al.)....Pages 154-161
Cardio-Pulmonary Substructure Segmentation of CT Images Using Convolutional Neural Networks (Rabia Haq, Alexandra Hotca, Aditya Apte, Andreas Rimner, Joseph O. Deasy, Maria Thor)....Pages 162-169
Back Matter ....Pages 171-172

✦ Subjects

Computer Science; Image Processing and Computer Vision; Health Informatics