most citedThe ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue

23 citations · 46 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2024★ 2 cited

PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery

Adrito Das, Danyal Z. Khan, Dimitrios Psychogyios +29

The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a sur…

cs.CV2024★ 6 cited

LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification

Reuben Dorent, Roya Khajavi, Tagwa Idris +24

Accurate assessment of lymph node size in 3D CT scans is crucial for cancer staging, therapeutic management, and monitoring treatment response. Existing state-of-the-art segmentati…

physics.med-ph2024★ 1 cited

Generating Synthetic Computed Tomography for Radiotherapy: SynthRAD2023 Challenge Report

Evi M. C. Huijben, Maarten L. Terpstra, Arthur Jr. Galapon +56

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomogra…

cs.CV2024★ 11 cited

SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge

Dimitrios Psychogyios, Emanuele Colleoni, Beatrice Van Amsterdam +47

Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to de…

cs.CV2023★ 2 cited

Domain generalization across tumor types, laboratories, and species -- insights from the 2022 edition of the Mitosis Domain Generalization Challenge

Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan +27

Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with…

eess.IV2023

Synthesizing 3D computed tomography from MRI or CBCT using 2.5D deep neural networks

Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa

Deep learning techniques, particularly convolutional neural networks (CNNs), have gained traction for synthetic computed tomography (sCT) generation from Magnetic resonance imaging…

eess.IV2023★ 23 cited

The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue

Philippe Weitz, Masi Valkonen, Leslie Solorzano +38

The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…

cs.CV2023★ 1 cited

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…

eess.IV2023

Unsupervised Domain Adaptation for MRI Volume Segmentation and Classification Using Image-to-Image Translation

Satoshi Kondo, Satoshi Kasai

Unsupervised domain adaptation is a type of domain adaptation and exploits labeled data from the source domain and unlabeled data from the target one. In the Cross-Modality Domain…