Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data
Manning College of Information and Computer Sciences, University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校曼宁信息与计算机科学学院）；Baystate Medical Center（贝斯州医疗中心）；UMass Chan Medical School - Baystate Campus（马萨诸塞大学陈医学院贝斯州校区）
Chiranjeewee Prasad Koirala, Sovesh Mohapatra, Advait Gosai, Gottfried Schlaug
Brain tumors, particularly glioblastoma, continue to challenge medical diagnostics and treatments globally. This paper explores the application of deep learning to multi-modality magnetic resonance imaging (MRI) data for enhanced brain tumor segmentation precision in the Sub-Saharan Africa patient population. We introduce an ensemble method that comprises eleven unique variations based on three core architectures: UNet3D, ONet3D, SphereNet3D and modified loss functions. The study emphasizes the need for both age- and population-based segmentation models, to fully account for the complexities in the brain. Our findings reveal that the ensemble approach, combining different architectures, outperforms single models, leading to improved evaluation metrics. Specifically, the results exhibit Dice scores of 0.82, 0.82, and 0.87 for enhancing tumor, tumor core, and whole tumor labels respectively. These results underline the potential of tailored deep learning techniques in precisely segmenting brain tumors and lay groundwork for future work to fine-tune models and assess performance across different brain regions.
Transferring Knowledge from High-Quality to Low-Quality MRI for Adult Glioma Diagnosis
The Chinese University of Hong Kong (CUHK)（香港中文大学）；CUHK Shenzhen Research Institute（香港中文大学深圳研究院）；China Medical University（中国医科大学）；University College London（伦敦大学学院）；UCL Hawkes Institute（伦敦大学学院霍克斯研究所）
Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma Dataset
Nepal Research and Collaboration Center (NRCC)（尼泊尔研究与合作中心）；Birendra Multiple Campus, Tribhuvan University（特里布万大学比伦德拉多校区）；Institute of Engineering, Purbanchal Campus, Tribhuvan University（特里布万大学普尔班查尔校区工程学院）；Bhaktapur Multiple Campus, Tribhuvan University（特里布万大学巴克塔普尔多校区）；Gandaki College of Engineering and Science, Pokhara University（博卡拉大学甘达基工程与科学学院）；McGill University（麦吉尔大学）；Lawson Health Research Institute（劳森健康研究所）；Medical Artificial Intelligence Laboratory (MAI Lab), Lagos（拉各斯医学人工智能实验室）；University of British Columbia（不列颠哥伦比亚大学）；Montreal Neurological Institute, McGill University（麦吉尔大学蒙特利尔神经学研究所）
Bridging the Gap: Generalising State-of-the-Art U-Net Models to Sub-Saharan African Populations
University of Cape Town（开普敦大学）；Stellenbosch University（斯泰伦博斯大学）；Lawson Health Research Institute（劳森健康研究院）；University of British Columbia（不列颠哥伦比亚大学）；McGill University（麦吉尔大学）
How We Won BraTS-SSA 2025: Brain Tumor Segmentation in the Sub-Saharan African Population Using Segmentation-Aware Data Augmentation and Model Ensembling
Kwame Nkrumah University of Science and Technology（卡布雷·克鲁马大学科学与技术大学）；University of Cape Coast（科克斯特大学）；University of Toronto（多伦多大学）；Department of Biomedical Engineering, McGill University（麦吉尔大学生物医学工程系）；Department of Physics, Federal University of Technology（联邦技术大学物理系）
Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data
Sheikh Zayed Institute for Pediatric Surgical Innovation（谢赫·扎耶德儿科外科创新研究所）；Children’s National Hospital（儿童国家医院）；Biomedical Image Technologies（生物医学影像技术中心）；Universidad Politécnica de Madrid（马德里理工大学）；CIBER-BBN（西班牙生物医学网络研究中心）；ISCIII（卡洛斯三世卫生研究所）；School of Medicine and Health Sciences, George Washington University（乔治·华盛顿大学医学与健康科学学院）
Towards SAMBA: Segment Anything Model for Brain Tumor Segmentation in Sub-Sharan African Populations
Nile University（尼罗大学）；Friedrich-Alexander-Universität（埃尔朗根-纽伦堡大学）；Makerere University（马凯雷雷大学）；Malawi University of Science and Technology（马拉维科技大学）；Medical Artificial Intelligence Laboratory (MAI Lab)（医学人工智能实验室（MAI Lab））；Lawson Health Research Institute（劳森健康研究院）；University of British Columbia（不列颠哥伦比亚大学）；Montreal Neurological Institute, McGill University（麦吉尔大学蒙特利尔神经学研究所）；University of Cape Town（开普敦大学）
How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation
University of Minho（米尼奥大学）；Institute for Artificial Intelligence in Medicine（人工智能医学研究所）；Graz University of Technology（格拉茨工业大学）；University Medicine Essen（埃森大学医学中心）；Cancer Research Center Cologne Essen (CCCE)（科隆-埃森癌症研究中心）；University Hospital Essen（埃森大学医院）；German Cancer Consortium (DKTK)（德国癌症联盟）
Topology-Driven Fusion of nnU-Net and MedNeXt for Accurate Brain Tumor Segmentation on Sub-Saharan Africa Dataset
Institute of Engineering, Thapathali Campus, Nepal（尼泊尔工程学院，塔帕塔利校区）；Gandaki College of Engineering and Science, Pokhara University, Pokhara, Nepal（加德基工程与科学学院，博克拉大学，博克拉，尼泊尔）；Nepal Engineering College, Changunarayan-4, Bhaktapur, Nepal（尼泊尔工程学院，恰纳拉亚纳-4，巴赫塔普尔，尼泊尔）；Madan Bhandari University of Science and Technology, Chitlang, Nepal（马丹·班达里科学与技术大学，奇塔朗，尼泊尔）；Montreal Neurological Institute, McGill University, Montreal, QC, Canada（蒙特利尔神经研究所，麦吉尔大学，蒙特利尔，魁北克，加拿大）；Department of Biomedical Engineering, McGill University（麦吉尔大学生物医学工程系）；Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria（医学人工智能实验室（MAI实验室），拉各斯，尼日利亚）；Department of Physics, Federal University of Technology, Minna, Nigeria（物理系，联邦技术大学，米纳，尼日利亚）；Department of Computer Science, Johns Hopkins University（计算机科学系，约翰霍普金斯大学）；Department of Radiology and Radiological Science, Johns Hopkins School of Medicine（放射学与放射科学系，约翰霍普金斯医学院）；Nepal Applied Mathematics and Informatics Institute for Research (NAAMII), Nepal（尼泊尔应用数学与信息学研究所（NAAMII），尼泊尔）；Institute of Engineering, Purbanchal Campus, Nepal（尼泊尔工程学院，普尔班恰尔校区）
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Medical Artificial Intelligence Laboratory (MAI Lab)（医学人工智能实验室（MAI实验室））；Department of Radiation Biology, Radiotherapy and Radiodiagnosis, University of Lagos（拉各斯大学放射生物学、放射治疗与放射诊断系）；Department of Radiology, University of California, San Diego（加州大学圣地亚哥分校放射科）；Crestview Radiology Limited（Crestview放射科有限公司）；Lagos University Teaching Hospital（拉各斯大学教学医院）；Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria（拉各斯州大学教学医院，伊凯贾，拉各斯，尼日利亚）；NSIA-Kano Diagnostic Center, Kano Nigeria（NSIA-卡诺诊断中心，卡诺，尼日利亚）；Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria（恩内迪·阿齐基韦大学教学医院，恩韦伊，安纳博拉州，尼日利亚）；Federal Medical Centre, Abeokuta, Ogun State, Nigeria（阿博库塔联邦医疗中心，奥贡州，尼日利亚）；Federal Medical Centre, Umahia, Abia State, Nigeria（乌马希亚联邦医疗中心，阿比亚州，尼日利亚）；National Hospital Abuja, FCT, Nigeria（阿布贾国家医院，联邦首都区，尼日利亚）；Benue State University Teaching Hospital, Markurdi, Benue State, Nigeria（贝努埃州大学教学医院，马库尔迪，贝努埃州，尼日利亚）；Duke University Medical Center, Department of Radiology, USA（达特茅斯大学医学中心，放射科，美国）；University of California San Francisco, CA, USA（加州大学旧金山分校，CA，美国）；Yale University, New Haven, CT, USA（耶鲁大学，新 Haven，CT，美国）；Children's National Hospital, Washington DC, USA（儿童医院华盛顿特区，华盛顿特区，美国）；George Washington University, Washington DC, USA（乔治·华盛顿大学，华盛顿特区，美国）；Sage Bionetworks, USA（Sage生物网络，美国）；Department of Neuroradiology, Technical University of Munich, Munich, Germany（慕尼黑技术大学神经放射科系，慕尼黑，德国）；Helmholtz Research Center, Munich, Germany（海德堡研究中心，慕尼黑，德国）；Duke University Medical Center, Department of Radiation Oncology, USA（达特茅斯大学医学中心，放射肿瘤科，美国）；Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA（费城儿童医院，宾夕法尼亚大学，费城，PA，美国）；Center for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA（人工智能与数据科学整合诊断中心（AI2D）及生物医学影像计算与分析中心（CBICA），宾夕法尼亚大学，费城，PA，美国）；Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA（Athinoula A Martinos生物医学影像中心，马萨诸塞总医院，波士顿，MA，美国）；University of Zurich, Switzerland（苏黎世大学，瑞士）；Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA（癌症成像计划，国家癌症研究所，国家卫生研究院，贝塞斯达，MD 20814，美国）；Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA（临床流行病学与生物统计学中心，宾夕法尼亚大学，费城，美国）；Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark（应用数学与计算机科学系，丹麦技术大学，丹麦）；Mayo Clinic, MN, USA（梅奥诊所，MN，美国）；Precision FDA, U.S. Food and Drug Administration, Silver Spring, MD, USA（Precision FDA，美国食品药品监督管理局，Silver Spring，MD，美国）；Booz Allen Hamilton, McLean, VA, USA（Booz Allen Hamilton，麦肯，VA，美国）；Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA（放射科，佩尔曼医学院，宾夕法尼亚大学，费城，PA，美国）；Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA（病理学与实验室医学系，佩尔曼医学院，宾夕法尼亚大学，费城，PA，美国）；Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA（全球健康中心，佩尔曼医学院，宾夕法尼亚大学，费城，宾夕法尼亚，美国）；Montreal Neurological Institute, McGill University, Montreal, Canada（蒙特利尔神经科学研究所，麦吉尔大学，蒙特利尔，加拿大）；Department of Medicine, University of Cape Town, South Africa（医学系，开普敦大学，南非）；Department of Radiation Medicine, University of Cape Town, South Africa（放射医学系，开普敦大学，南非）
A New Logic For Pediatric Brain Tumor Segmentation
1 Northwestern University, Feinberg School of Medicine, Chicago IL, USA 2 Children’s National Hospital, Sheikh Zayed Institute for Pediatric Surgical Innovation, Washington, DC, USA 3 Ann \& Robert H Lurie Children's Hospital of Chicago, Chicago, IL, USA
Reutlingen University（罗伊特林根大学）；Menoufia University（梅努菲亚大学）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）
Automatic segmentation is essential for the brain tumor diagnosis, disease prognosis, and follow-up therapy of patients with gliomas. Still, accurate detection of gliomas and their sub-regions in multimodal MRI is very challenging due to the variety of scanners and imaging protocols. Over the last years, the BraTS Challenge has provided a large number of multi-institutional MRI scans as a benchmark for glioma segmentation algorithms. This paper describes our contribution to the BraTS 2022 Continuous Evaluation challenge. We propose a new ensemble of multiple deep learning frameworks namely, De…
Generative Style Transfer for MRI Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan Africa
Institute of Mathematical Science, Strathmore University（斯特拉斯莫尔大学数学科学学院）；Faculty of Science and Engineering, University of Hull（赫尔大学科学与工程学院）；Technical University of Mombasa（蒙巴萨理工大学）；Lawson Health Research Institute（劳森健康研究所）；University of British Columbia（不列颠哥伦比亚大学）；University of Nairobi（内罗毕大学）；University of Cape Town（开普敦大学）；Montreal Neurological Institute, McGill University（麦吉尔大学蒙特利尔神经学研究所）；Brain Mind Institute, The Aga Khan University（阿迦汗大学脑与心智研究所）；Medical Physics Unit, McGill University（麦吉尔大学医学物理部门）
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Center for Data-Driven Discovery in Biomedicine (D3b), Children’s Hospital of Philadelphia（费城儿童医院生物医学数据驱动发现中心）；University of Pennsylvania（宾夕法尼亚大学）；Center for AI & Data Science for Integrated Diagnostics (AI2D)（综合诊断人工智能与数据科学中心）；Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania（宾夕法尼亚大学生物医学图像计算与分析中心）；Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital（儿童医院谢赫·扎耶德儿科外科创新研究所）；Thomas Jefferson University Hospital（托马斯杰斐逊大学医院）；Sage Bionetworks；Montreal Neurological Institute (MNI), McGill University（麦吉尔大学蒙特利尔神经学研究所）；Perelman School of Medicine, University of Pennsylvania（宾夕法尼亚大学佩雷尔曼医学院）；University of Southern California（南加州大学）；Duke University Medical Center（杜克大学医学中心）；Mayo Clinic（梅奥诊所）；Center for Global Health, Perelman School of Medicine, University of Pennsylvania（宾夕法尼亚大学佩雷尔曼医学院全球健康中心）；Technical University of Munich（慕尼黑工业大学）；TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich（慕尼黑工业大学转化肿瘤学研究中心（TranslaTUM））；National Cancer Institute（美国国家癌症 Institute）
Deep Ensemble approach for Enhancing Brain Tumor Segmentation in Resource-Limited Settings
University of Ibadan（伊巴丹大学）；African Institute for Mathematical Sciences（非洲数学科学研究所）；University of Cape Town（开普敦大学）；South African National Bioinformatics Institute（南非国家生物信息学研究所）；University of Western Cape（西开普大学）；Carnegie Mellon University（卡内基梅隆大学）；McGill University（麦吉尔大学）；Lawson Health Research Institute（劳森健康研究所）；University of British Columbia（不列颠哥伦比亚大学）
Deformable image registration is a key task in medical image analysis. The Brain Tumor Sequence Registration challenge (BraTS-Reg) aims at establishing correspondences between pre-operative and follow-up scans of the same patient diagnosed with an adult brain diffuse high-grade glioma and intends to address the challenging task of registering longitudinal data with major tissue appearance changes. In this work, we proposed a two-stage cascaded network based on the Inception and TransMorph models. The dataset for each patient was comprised of a native pre-contrast (T1), a contrast-enhanced T1-w…
Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）
Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use o…
Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-Guided Subtyping and Lesion-Wise Model Ensemble
Sheikh Zayed Institute for Pediatric Surgical Innovation（Sheikh Zayed儿童外科创新研究所）；Children’s National Hospital（儿童医院）；University of Washington（华盛顿大学）；Universidad Politécnica de Madrid（马德里理工大学）；CIBER-BBN；ISCIII；School of Medicine and Health Sciences（医学与健康科学学院）
Training Beyond Convergence: Grokking nnU-Net for Glioma Segmentation in Sub-Saharan MRI
Multimedia University（多媒体大学）；University of British Columbia（不列颠哥伦比亚大学）；McGill University（麦吉尔大学）；Montreal Neurological Institute（蒙特利尔神经学研究所）；Federal University of Technology Minna（明纳联邦理工大学）；Medical Artificial Intelligence Laboratory（医学人工智能实验室）；Friedrich-Alexander-Universität（弗里德里希-亚历山大大学）
