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ORCIDBraTS/CrossMoDA@MICCAI 2023: Vancouver, BC, Canada
- Ujjwal Baid, Reuben Dorent, Sylwia Malec, Monika Pytlarz, Ruisheng Su
, Navodini Wijethilake, Spyridon Bakas, Alessandro Crimi:
Brain Tumor Segmentation, and Cross-Modality Domain Adaptation for Medical Image Segmentation - MICCAI Challenges, BraTS 2023 and CrossMoDA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12 and 8, 2024, Proceedings. Lecture Notes in Computer Science 14669, Springer 2024, ISBN 978-3-031-76162-1
BraTS
- Jiayu Huo, Chih-Yang Li, Alejandro Granados, Sébastien Ourselin, Rachel Sparks:
Unleash the Power of 2D Pre-trained Model for 3D T1-weighted Brain MRI Inpainting. 3-10 - David Bouget, André Pedersen, Ole Solheim, Ingerid Reinertsen:
The AGU-Net Architecture for Brain Tumor Segmentation: BraTS Challenges 2023. 11-23 - Ramy A. Zeineldin, Franziska Mathis-Ullrich:
Ensemble Learning and 3D Pix2Pix for Comprehensive Brain Tumor Analysis in Multimodal MRI. 24-34 - Alicia Durrer, Philippe C. Cattin, Julia Wolleb:
Denoising Diffusion Models for Inpainting of Healthy Brain Tissue. 35-45 - Yubo Zhou, Lanfeng Zhong, Guotai Wang:
Brain Tumor Segmentation Based on Self-supervised Pre-training and Adaptive Region-Specific Loss. 46-57 - Ivo M. Baltruschat, Parvaneh Janbakhshi, Matthias Lenga:
BraSyn 2023 Challenge: Missing MRI Synthesis and the Effect of Different Learning Objectives. 58-68 - Agus Subhan Akbar, Ahmad Hayam Brilian, Chastine Fatichah, Nanik Suciati:
Previous Datasets Performance for Brain Tumor Segmentation of BraTS 2023 Current Dataset. 69-78 - André Ferreira, Naida Solak, Jianning Li, Philipp Dammann, Jens Kleesiek, Victor Alves, Jan Egger:
Enhanced Data Augmentation Using Synthetic Data for Brain Tumour Segmentation. 79-93 - Ziya Ata Yazici, Ilkay Öksüz, Hazim Kemal Ekenel:
Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation. 94-105 - Jiahao Zheng, Liqin Huang:
3D ST-Net: A Large Kernel Simple Transformer for Brain Tumor Segmentation. 106-116 - Xiao Yang, Shaohua Zheng:
Multimodal Brain Tumor Segmentation Using Modified 3D UNet3+ Architecture. 117-127 - Yi Li, Zhirui Fang, Di Li, Xin Xie, Yanqing Guo:
Enhancing Encoder with Attention Gate for Multimodal Brain Tumor Segmentation. 128-139 - Ziyan Huang, Jin Ye, Haoyu Wang, Zhongying Deng, Yanzhou Su, Tianbin Li, Junlong Cheng, Jianpin Chen, Sizheng Guo, Yiqing Shen, Junjun He:
Evaluating STU-Net for Brain Tumor Segmentation. 140-151 - Kameswara Bharadwaj Mantha, Ramanakumar Sankar, Lucy Fortson:
Automated 3D Tumor Segmentation Using Temporal Cubic PatchGAN (TCuP-GAN). 152-164 - Tianyi Ren, Ethan Honey, Harshitha Rebala, Abhishek Sharma, Agamdeep Chopra, Mehmet Kurt:
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor Segmentation. 165-176 - Ayhan Can Erdur, Daniel Scholz, Josef A. Buchner, Stephanie E. Combs, Daniel Rueckert, Jan C. Peeken:
All Sizes Matter: Improving Volumetric Brain Segmentation on Small Lesions. 177-189 - Siwei Yang, Xianhang Li, Jieru Mei, Jieneng Chen, Cihang Xie, Yuyin Zhou:
3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 Challenge. 190-199 - Mohannad Barakat, Noha Magdy, Jjuuko George William, Ethel Phiri, Raymond Confidence, Dong Zhang, Udunna C. Anazodo:
Towards SAMBA: Segment Anything Model for Brain Tumor Segmentation in Sub-Saharan African Populations. 200-210 - Shashidhar Reddy Javaji, Advait Gosai, Sovesh Mohapatra, Gottfried Schlaug:
Automated Ensemble Method for Pediatric Brain Tumor Segmentation. 211-220 - Daniel Capellán-Martín, Zhifan Jiang, Abhijeet Parida, Xinyang Liu, Van Lam, Hareem Nisar, Austin Tapp, Sarah Elsharkawi, María J. Ledesma-Carbayo, Syed Muhammad Anwar, Marius George Linguraru:
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance Imaging. 221-232 - Juexin Zhang, Ke Chen, Ying Weng:
Synthesis of Healthy Tissue Within Tumor Area via U-Net. 233-240 - Alyssa R. Amod, Alexandra Smith, Pearly Joubert, Raymond Confidence, Dong Zhang, Udunna C. Anazodo, Dodzi Motchon, Tinashe E. M. Mutsvangwa, Sébastien Quetin:
Bridging the Gap: Generalising State-of-the-Art U-Net Models to Sub-Saharan African Populations. 241-254 - Valeriia Abramova, Uma M. Lal-Trehan Estrada, Cansu Yalcin, Rachika E. Hamadache, Albert Clèrigues, Francisco Aarón Tovar Sáez, Marc Guirao, Joaquim Salvi, Arnau Oliver, Xavier Lladó:
nnUNet for Brain Tumor Segmentation in Sub-Saharan Africa Patient Population. 255-263 - Fadillah A. Maani, Anees Ur Rehman Hashmi, Mariam Aljuboory, Numan Saeed, Ikboljon Sobirov, Mohammad Yaqub:
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks. 264-277 - Sahaj K. Mistry, Aayush Gupta, Sourav Saini, Aashray Gupta, Sunny Rai, Vinit Jakhetiya, Ujjwal Baid, Sharath Chandra Guntuku:
Multiscale Encoder and Omni-Dimensional Dynamic Convolution Enrichment in nnU-Net for Brain Tumor Segmentation. 278-290 - Hui Lin, Xi Cheng, Ziru Chen:
MenUnet: An End-to-End 3D Neural Network for Meningioma Segmentation from Multiparametric MRI. 291-299 - Anita Kriz, Raghav Mehta, Brennan Nichyporuk, Tal Arbel:
Exploring Compound Loss Functions for Brain Tumor Segmentation. 300-311 - Md. Shibly Sadique, Md Monibor Rahman, Walia Farzana, Alexander Glandon, Ahmed G. Temtam, Khan M. Iftekharuddin:
Local Synthesis of Healthy Brain Tissue Using an Enhanced 3D Pix2Pix Model for Medical Image Inpainting. 312-321 - Md. Shibly Sadique, Md Monibor Rahman, Walia Farzana, Alexander Glandon, Ahmed G. Temtam, Khan M. Iftekharuddin:
Brain Tumor Segmentation: Glioma Segmentation in Sub-Saharan Africa Patients Using nnU-Net. 322-331 - Ahmed G. Temtam, Md. Shibly Sadique, Md Monibor Rahman, Walia Farzana, Khan M. Iftekharuddin:
Pediatric Brain Tumor Segmentation Using Multiresolution Fractal Deep Neural Network. 332-340 - José Armando Hernández:
BPML, MLops and 3D-UNet Network Integration in End-to-End Application Design Applied to the Segmentation of Human Brain Tumors in Clinic Cases. 341-351
CrossMoDA
- Cancan Chen, Dawei Wang, Rongguo Zhang:
An Efficient Cross-Modal Segmentation Method for Vestibular Schwannoma and Cochlea on MRI Images. 355-363 - Luyi Han, Tao Tan, Ritse Mann:
Fine-Grained Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation. 364-371 - Han Liu, Yubo Fan, Zhoubing Xu, Benoit M. Dawant, Ipek Oguz:
Learning Site-Specific Styles for Multi-institutional Unsupervised Cross-Modality Domain Adaptation. 372-385 - Ziyuan Zhao, Ruikai Lin, Kaixin Xu, Xulei Yang, Cuntai Guan:
MS-MT++: Enhanced Multi-scale Mean Teacher for Cross-Modality Vestibular Schwannoma and Cochlea Segmentation. 386-394
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