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ORCID5th Brainles@MICCAI 2019: Shenzhen, China - Part II
- Alessandro Crimi
, Spyridon Bakas:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part II. Lecture Notes in Computer Science 11993, Springer 2020, ISBN 978-3-030-46642-8
Brain Tumor Image Segmentation
- Xiaowei Xu, Wangyuan Zhao, Jun Zhao:
Brain Tumor Segmentation Using Attention-Based Network in 3D MRI Images. 3-13 - Woo-Sup Han, Il Song Han:
Multimodal Brain Image Segmentation and Analysis with Neuromorphic Attention-Based Learning. 14-26 - Guojing Zhao, Jianpeng Zhang, Yong Xia:
Improving Brain Tumor Segmentation in Multi-sequence MR Images Using Cross-Sequence MR Image Generation. 27-36 - Subhashis Banerjee, Harkirat Singh Arora, Sushmita Mitra:
Ensemble of CNNs for Segmentation of Glioma Sub-regions with Survival Prediction. 37-49 - Xutao Guo, Chushu Yang, Ting Ma, PengZheng Zhou, Shangfeng Lu, Nan Ji, Deling Li, Tong Wang, Haiyan Lv:
Brain Tumor Segmentation Based on Attention Mechanism and Multi-model Fusion. 50-60 - Shuo Wang, Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction. 61-72 - Linmin Pei, Lasitha Vidyaratne, Md Monibor Rahman, Zeina A. Shboul, Khan M. Iftekharuddin:
Multimodal Brain Tumor Segmentation and Survival Prediction Using Hybrid Machine Learning. 73-81 - Andriy Myronenko, Ali Hatamizadeh:
Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIs. 82-89 - Ujjwal Baid, Nisarg A. Shah, Sanjay N. Talbar:
Brain Tumor Segmentation with Cascaded Deep Convolutional Neural Network. 90-98 - Chandan Ganesh Bangalore Yogananda, Benjamin C. Wagner, Sahil S. Nalawade, Gowtham Krishnan Murugesan, Marco C. Pinho, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian:
Fully Automated Brain Tumor Segmentation and Survival Prediction of Gliomas Using Deep Learning and MRI. 99-112 - S. Rosas González, Taibou Birgui Sekou, Moncef Hidane, Clovis Tauber:
3D Automatic Brain Tumor Segmentation Using a Multiscale Input U-Net Network. 113-123 - Sveinn Pálsson, Stefano Cerri, Andrea Dittadi, Koen Van Leemput:
Semi-supervised Variational Autoencoder for Survival Prediction. 124-134 - Pablo Ribalta Lorenzo, Michal Marcinkiewicz, Jakub Nalepa:
Multi-modal U-Nets with Boundary Loss and Pre-training for Brain Tumor Segmentation. 135-147 - Gowtham Krishnan Murugesan, Sahil S. Nalawade, Chandan Ganesh Bangalore Yogananda, Benjamin C. Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian:
Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation. 148-157 - Parvez Ahmad, Saqib Qamar, Seyed Raein Hashemi, Linlin Shen:
Hybrid Labels for Brain Tumor Segmentation. 158-166 - Thibault Buatois, Élodie Puybareau, Guillaume Tochon, Joseph Chazalon:
Two Stages CNN-Based Segmentation of Gliomas, Uncertainty Quantification and Prediction of Overall Patient Survival. 167-178 - Krzysztof Kotowski, Jakub Nalepa, Wojciech Dudzik:
Detection and Segmentation of Brain Tumors from MRI Using U-Nets. 179-190 - Nabila Abraham, Naimul Mefraz Khan:
Multimodal Segmentation with MGF-Net and the Focal Tversky Loss Function. 191-198 - Kaisheng Liang, Wenlian Lu:
Brain Tumor Segmentation Using 3D Convolutional Neural Network. 199-207 - Hanxiao Zhang, Jingxiong Li, Mali Shen, Yaqi Wang, Guang-Zhong Yang:
DDU-Nets: Distributed Dense Model for 3D MRI Brain Tumor Segmentation. 208-217 - Megh Bhalerao, Siddhesh Thakur:
Brain Tumor Segmentation Based on 3D Residual U-Net. 218-225 - Yan-Ting Weng, Hsiang-Wei Chan, Teng-Yi Huang:
Automatic Segmentation of Brain Tumor from 3D MR Images Using SegNet, U-Net, and PSP-Net. 226-233 - Kai Yan, Qiuchang Sun, Ling Li, Zhicheng Li:
3D Deep Residual Encoder-Decoder CNNS with Squeeze-and-Excitation for Brain Tumor Segmentation. 234-243 - Yanhao Ren, Pin Sun, Wenlian Lu:
Overall Survival Prediction Using Conventional MRI Features. 244-254 - Yunzhe Xue, Meiyan Xie, Fadi G. Farhat, Olga Boukrina, A. M. Barrett, Jeffrey R. Binder, Usman W. Roshan, William W. Graves:
A Multi-path Decoder Network for Brain Tumor Segmentation. 255-265 - Pengyu Yin, Yingdong Hu, Jing Liu, Jiaming Duan, Wei Yang, Kun Cheng:
The Tumor Mix-Up in 3D Unet for Glioma Segmentation. 266-273 - Guohua Cheng, Mengyan Luo, Linyang He, Lingqiang Mo:
Multi-branch Learning Framework with Different Receptive Fields Ensemble for Brain Tumor Segmentation. 274-284 - Xiaoqing Guo, Chen Yang, Pak Lun Lam, Yat Ming Peter Woo, Yixuan Yuan:
Domain Knowledge Based Brain Tumor Segmentation and Overall Survival Prediction. 285-295 - Andrei Iantsen, Vincent Jaouen, Dimitris Visvikis, Mathieu Hatt:
Encoder-Decoder Network for Brain Tumor Segmentation on Multi-sequence MRI. 296-302 - Mostefa Ben Naceur, Mohamed Akil, Rachida Saouli, Rostom Kachouri:
Deep Convolutional Neural Networks for Brain Tumor Segmentation: Boosting Performance Using Deep Transfer Learning: Preliminary Results. 303-315 - Mehdi Astaraki, Chunliang Wang, Gabriel Carrizo, Iuliana Toma-Dasu, Örjan Smedby:
Multimodal Brain Tumor Segmentation with Normal Appearance Autoencoder. 316-323 - Dmitry A. Lachinov, Elena Shipunova, Vadim Turlapov:
Knowledge Distillation for Brain Tumor Segmentation. 324-332
Combined MRI and Pathology Brain Tumor Classification
- Linmin Pei, Lasitha Vidyaratne, Wei-Wen Hsu, Md Monibor Rahman, Khan M. Iftekharuddin:
Brain Tumor Classification Using 3D Convolutional Neural Network. 335-342 - Xiao Ma, Fucang Jia:
Brain Tumor Classification with Multimodal MR and Pathology Images. 343-352 - Hsiang-Wei Chan, Yan-Ting Weng, Teng-Yi Huang:
Automatic Classification of Brain Tumor Types with the MRI Scans and Histopathology Images. 353-359 - Yunzhe Xue, Yanan Yang, Fadi G. Farhat, Frank Y. Shih, Olga Boukrina, A. M. Barrett, Jeffrey R. Binder, William W. Graves, Usman W. Roshan:
Brain Tumor Classification with Tumor Segmentations and a Dual Path Residual Convolutional Neural Network from MRI and Pathology Images. 360-367
Tools AllowingClinical Translation of Image Computing Algorithms
- Tahsin M. Kurç, Ashish Sharma, Rajarsi Gupta, Le Hou, Han Le, Shahira Abousamra, Erich Bremer, Ryan Birmingham, Tammy Diprima, Nan Li, Feiqiao Wang, Joseph Balsamo, Whitney Bremer, Dimitris Samaras, Joel H. Saltz:
From Whole Slide Tissues to Knowledge: Mapping Sub-cellular Morphology of Cancer. 371-379 - Sarthak Pati, Ashish Singh, Saima Rathore, Aimilia Gastounioti, Mark Bergman, Phuc Ngo, Sung Min Ha, Dimitrios Bounias, James Minock, Grayson Murphy, Hongming Li, Amit Bhattarai, Adam Wolf, Patmaa Sridaran, Ratheesh Kalarot, Hamed Akbari, Aristeidis Sotiras, Siddhesh P. Thakur, Ragini Verma, Russell T. Shinohara, Paul A. Yushkevich, Yong Fan, Despina Kontos, Christos Davatzikos, Spyridon Bakas:
The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview. 380-394
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