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20232025
most citedUnderstanding metric-related pitfalls in image analysis validation

204 citations · 415 across the 17 of their papers we have counts for

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10 papers · 1 filter

eess.IV2023★ 6 cited

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network

Ariana M. Familiar, Anahita Fathi Kazerooni, Hannah Anderson +37

Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the…

eess.IV2023★ 1 cited

AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons

Gowtham Krishnan Murugesan, Diana McCrumb, Mariam Aboian +10

The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging too…

q-bio.OT2023★ 30 cited

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

Ahmed W. Moawad, Anastasia Janas, Ujjwal Baid +229

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS…

eess.IV2023★ 38 cited

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)

Maruf Adewole, Jeffrey D. Rudie, Anu Gbadamosi +48

Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 ye…

cs.CV2023★ 27 cited

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma

Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta +57

Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists,…

eess.IV2023★ 44 cited

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu +70

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less…

eess.IV2023★ 12 cited

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)

Hongwei Bran Li, Gian Marco Conte, Qingqiao Hu +62

Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input m…

eess.IV2023★ 4 cited

The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

Florian Kofler, Felix Meissen, Felix Steinbauer +103

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…

cs.CR2023★ 14 cited

Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations

David A. Clunie, Adam Flanders, Adam Taylor +16

This report addresses the technical aspects of de-identification of medical images of human subjects and biospecimens, such that re-identification risk of ethical, moral, and legal…

cs.CV2023★ 204 cited

Understanding metric-related pitfalls in image analysis validation

Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…