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Found 26 papers, 5 papers with code
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications.
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
Why is the winner the best?
The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning.
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.
Automated Lesion Segmentation in Whole-Body FDG-PET/CT with Multi-modality Deep Neural Networks
To promote research on machine learning-based automated tumor lesion segmentation on whole-body FDG-PET/CT data, Automated Lesion Segmentation in Whole-Body FDG-PET/CT (autoPET) challenge is held, and a large, publicly available training dataset is provided.
Unsupervised Domain Adaptation for MRI Volume Segmentation and Classification Using Image-to-Image Translation
Unsupervised domain adaptation is a type of domain adaptation and exploits labeled data from the source domain and unlabeled data from the target one.
CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection
This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection.
AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge
Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible.
Biomedical image analysis competitions: The state of current participation practice
Of these, 84% were based on standard architectures.
Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge
Using this publicly available dataset and results as a springboard, future work may enable more efficient training of surgeons with advances in surgical data science.
Source-Free Unsupervised Domain Adaptation with Norm and Shape Constraints for Medical Image Segmentation
In general, UDA assumes that all samples from source and target domains are available during the training process.
A Two Step Approach for Whole Slide Image Registration
Multi-stain whole-slide-image (WSI) registration is an active field of research.
Multi-Modality Abdominal Multi-Organ Segmentation with Deep Supervised 3D Segmentation Model
To promote the development of medical image segmentation technology, AMOS, a large-scale abdominal multi-organ dataset for versatile medical image segmentation, is provided and AMOS 2022 challenge is held by using the dataset.
CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
In this paper, we present the challenge setup and assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge.
Ranked #1 on
Action Triplet Recognition
on CholecT50 (Challenge)
(using extra training data)
Mitosis domain generalization in histopathology images -- The MIDOG challenge
The goal of the MICCAI MIDOG 2021 challenge has been to propose and evaluate methods that counter this domain shift and derive scanner-agnostic mitosis detection algorithms.
Computer Aided Diagnosis and Out-of-Distribution Detection in Glaucoma Screening Using Color Fundus Photography
Artificial Intelligence for RObust Glaucoma Screening (AIROGS) Challenge is held for developing solutions for glaucoma screening from color fundus photography that are robust to real-world scenarios.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Nuclei panoptic segmentation and composition regression with multi-task deep neural networks
Nuclear segmentation, classification and quantification within Haematoxylin & Eosin stained histology images enables the extraction of interpretable cell-based features that can be used in downstream explainable models in computational pathology.
PEg TRAnsfer Workflow recognition challenge report: Does multi-modal data improve recognition?
The improvement between video/kinematic-based methods and the uni-modality ones was significant for all of the teams.
Ranked #1 on
Semantic Segmentation
on PETRAW
Kinematic Based Workflow Recognition
Segmentation Based Workflow Recognition
+4
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation
The aim was to automatically perform unilateral VS and bilateral cochlea segmentation on hrT2 as provided in the testing set (N=137).
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems.
Ranked #1 on
Surgical phase recognition
on HeiChole Benchmark
Multi-source Domain Adaptation Using Gradient Reversal Layer for Mitotic Cell Detection
This is a write-up of our method submitted to Mitosis Domain Generalization (MIDOG 2021) Challenge held in MICCAI2021 conference.
MIcro-Surgical Anastomose Workflow recognition challenge report
The best models achieved more than 95% AD-Accuracy for phase recognition, 80% for step recognition, 60% for activity recognition, and 75% for all granularity levels.
Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
Surgical data science is revolutionizing minimally invasive surgery by enabling context-aware applications.
Arithmetic quotients of the Bruhat-Tits building for projective general linear group in positive characteristic
For the other theorem (Theorem 12), we construct, using the geometry of the Bruhat-Tits building, an analogue of modular symbols in $\mathcal{A}_{\mathrm{St}}$ integrally (that is, in the space of $\mathbb{Z}$-valued automorphic forms).
Number Theory 11F67 11F70 (Primary) 20E42 (Secondary)
2018 Robotic Scene Segmentation Challenge
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models.
Assessment of algorithms for mitosis detection in breast cancer histopathology images
The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers.
