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View article: The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods Open
We present the design and results of the MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024, which focuses on federated learning (FL) for glioma sub-region segmentation in multi-parametric MRI scans. Unlike previous FeTS challenges,…
View article: IMG-69. FeTS 2.0: Federated learning sets benchmark in post-op GBM segmentation
IMG-69. FeTS 2.0: Federated learning sets benchmark in post-op GBM segmentation Open
BACKGROUND Progress in automated volumetric segmentation of postoperative glioblastoma has been hindered by limited data availability, primarily related to patient privacy concerns. To overcome this, we developed the Federated Tumor Segmen…
View article: IMG-121. BraTS-Pathology 2024: Insights and Future Directions Informed by the AI-RANO & RANO-RGP Effort to Assess Glioblastoma Heterogeneity
IMG-121. BraTS-Pathology 2024: Insights and Future Directions Informed by the AI-RANO & RANO-RGP Effort to Assess Glioblastoma Heterogeneity Open
INTRODUCTION Glioblastoma is the most common malignant adult brain tumor with poor prognosis, largely due to its heterogeneous landscape. The AI-RANO and RANO-RGP groups organized the BraTS-Pathology 2024 challenge, providing a publicly-av…
View article: DENTEX Challenge 2023 Proceedings: Participant Short Papers
DENTEX Challenge 2023 Proceedings: Participant Short Papers Open
Website: https://dentex.grand-challenge.orgContact Author: Ibrahim Ethem Hamamci (University of Zurich) [email protected]: Ibrahim Ethem Hamamci, Sezgin Er, Ezequiel de la Rosa, Kaiyuan Yang, Hongwei Li, Albert Mehl, Bernd S…
View article: Informatics at the Frontier of Cancer Research
Informatics at the Frontier of Cancer Research Open
Digitized healthcare data, high-throughput profiling technologies, and data repositories have facilitated the emergence of a new era of cancer research. Each data stream requires specialized analysis methods for interpretation. The data-dr…
View article: BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023 Open
Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-i…
View article: An Unsupervised Brain Extraction Quality Control Approach for Efficient Neuro-Oncology Studies
An Unsupervised Brain Extraction Quality Control Approach for Efficient Neuro-Oncology Studies Open
Brain extraction is essential in neuroimaging studies for patient privacy and optimizing computational analyses. Manual creation of 3D brain masks is labor-intensive, prompting the development of automatic computational methods. Robust qua…
View article: BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis
BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis Open
The Brain Tumor Segmentation (BraTS) cluster of challenges has significantly advanced brain tumor image analysis by providing large, curated datasets and addressing clinically relevant tasks. However, despite its success and popularity, al…
View article: Inclusive, Differentially Private Federated Learning for Clinical Data
Inclusive, Differentially Private Federated Learning for Clinical Data Open
Federated Learning (FL) offers a promising approach for training clinical AI models without centralizing sensitive patient data. However, its real-world adoption is hindered by challenges related to privacy, resource constraints, and compl…
View article: Adapting to evolving MRI data: A transfer learning approach for Alzheimer’s disease prediction
Adapting to evolving MRI data: A transfer learning approach for Alzheimer’s disease prediction Open
Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer's Disease (AD). However, changes in MRI technologies and acquisition protocols often yield l…
View article: Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning
Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning Open
PURPOSE Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast d…
View article: TMIC-60. BRATS-PATH: ASSESSING HETEROGENEOUS HISTOPATHOLOGIC REGIONS IN GLIOBLASTOMA
TMIC-60. BRATS-PATH: ASSESSING HETEROGENEOUS HISTOPATHOLOGIC REGIONS IN GLIOBLASTOMA Open
Glioblastoma, the most common malignant primary adult brain tumor, poses significant diagnostic and treatment challenges due to its heterogeneous molecular and micro-environmental profiles. To this end, we organize the BraTS-Path challenge…
View article: GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio)Medical Imaging
GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio)Medical Imaging Open
Generative Artificial Intelligence (GenAI) is a field of AI that creates new data samples from existing ones. It utilizing deep learning to overcome the scarcity and regulatory constraints of healthcare data by generating new data points t…
View article: Image segmentations produced by BAMF under the AIMI Annotations initiative
Image segmentations produced by BAMF under the AIMI Annotations initiative Open
The Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov/) [1] connects researchers with publicly available cancer imaging data, often linked with other types of cancer data. Many of the collections have limited annotations du…
View article: Best practices to evaluate the impact of biomedical research software—metric collection beyond citations
Best practices to evaluate the impact of biomedical research software—metric collection beyond citations Open
Motivation Software is vital for the advancement of biology and medicine. Impact evaluations of scientific software have primarily emphasized traditional citation metrics of associated papers, despite these metrics inadequately capturing t…
View article: BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023 Open
Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-i…
View article: Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge Open
The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional dataset of 750 radiotherapy planning brain MRIs with expert-a…
View article: BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions
BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions Open
Glioblastoma is the most common primary adult brain tumor, with a grim prognosis - median survival of 12-18 months following treatment, and 4 months otherwise. Glioblastoma is widely infiltrative in the cerebral hemispheres and well-define…
View article: The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights
The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights Open
Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts…
View article: Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps Open
This paper introduces panoptica, a versatile and performance-optimized package designed for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. panoptica addresses the limitations of existing metrics and …
View article: Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?
Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful? Open
Software is vital for the advancement of biology and medicine. Analysis of usage and impact metrics can help developers determine user and community engagement, justify additional funding, encourage additional use, identify unanticipated u…
View article: Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?
Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful? Open
Software is vital for the advancement of biology and medicine. Through analysis of usage and impact metrics of software, developers can help determine user and community engagement. These metrics can be used to justify additional funding, …
View article: Why is the Winner the Best?
Why is the Winner the Best? Open
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do …