research
∙
09/18/2023
Application-driven Validation of Posteriors in Inverse Problems
Current deep learning-based solutions for image analysis tasks are commo...
share
research
∙
07/14/2023
Challenge Results Are Not Reproducible
While clinical trials are the state-of-the-art methods to assess the eff...
research
∙
05/11/2023
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge
The ability to automatically detect and track surgical instruments in en...
research
∙
03/22/2023
Self-distillation for surgical action recognition
Surgical scene understanding is a key prerequisite for contextaware deci...
research
∙
03/22/2023
Deployment of Image Analysis Algorithms under Prevalence Shifts
Domain gaps are among the most relevant roadblocks in the clinical trans...
research
∙
03/20/2023
Semantic segmentation of surgical hyperspectral images under geometric domain shifts
Robust semantic segmentation of intraoperative image data could pave the...
research
∙
03/17/2023
Unsupervised Domain Transfer with Conditional Invertible Neural Networks
Synthetic medical image generation has evolved as a key technique for ne...
research
∙
02/13/2023
CholecTriplet2022: Show me a tool and tell me the triplet – an endoscopic vision challenge for surgical action triplet detection
Formalizing surgical activities as triplets of the used instruments, act...
research
∙
12/08/2022
Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge
Timely and effective feedback within surgical training plays a critical ...
research
∙
11/17/2022
Sources of performance variability in deep learning-based polyp detection
Validation metrics are a key prerequisite for the reliable tracking of s...
research
∙
11/04/2022
MONAI: An open-source framework for deep learning in healthcare
Artificial Intelligence (AI) is having a tremendous impact across most a...
research
∙
12/15/2021
Ten years of image analysis and machine learning competitions in dementia
Machine learning methods exploiting multi-parametric biomarkers, especia...
research
∙
11/09/2021
Robust deep learning-based semantic organ segmentation in hyperspectral images
Semantic image segmentation is an important prerequisite for context-awa...
research
∙
09/30/2021
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 t...
research
∙
07/08/2021
Task Fingerprinting for Meta Learning in Biomedical Image Analysis
Shortage of annotated data is one of the greatest bottlenecks in biomedi...
research
∙
06/15/2021
Machine learning-based analysis of hyperspectral images for automated sepsis diagnosis
Sepsis is a leading cause of mortality and critical illness worldwide. W...
research
∙
05/28/2021
Video-rate multispectral imaging in laparoscopic surgery: First-in-human application
Multispectral and hyperspectral imaging (MSI/HSI) can provide clinically...
research
∙
05/20/2021
Semantic segmentation of multispectral photoacoustic images using deep learning
Photoacoustic imaging has the potential to revolutionise healthcare due ...
research
∙
05/12/2021
The Federated Tumor Segmentation (FeTS) Challenge
This manuscript describes the first challenge on Federated Learning, nam...
research
∙
04/12/2021
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is increasing at an eno...
research
∙
03/29/2021
Data-driven generation of plausible tissue geometries for realistic photoacoustic image synthesis
Photoacoustic tomography (PAT) has the potential to recover morphologica...
research
∙
02/26/2021
Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
Surgical data science is revolutionizing minimally invasive surgery by e...
research
∙
01/04/2021
Stereo Correspondence and Reconstruction of Endoscopic Data Challenge
The stereo correspondence and reconstruction of endoscopic data sub-chal...
research
∙
12/22/2020
SERV-CT: A disparity dataset from CT for validation of endoscopic 3D reconstruction
In computer vision, reference datasets have been highly successful in pr...
research
∙
12/15/2020
Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
Image registration is the basis for many applications in the fields of m...
research
∙
11/10/2020
Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging
Multispectral photoacoustic imaging (PAI) is an emerging imaging modalit...
research
∙
11/10/2020
Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern
Purpose: Photoacoustic tomography (PAT) is a novel imaging technique tha...
research
∙
11/05/2020
Deep learning for biomedical photoacoustic imaging: A review
Photoacoustic imaging (PAI) is a promising emerging imaging modality tha...
research
∙
05/07/2020
Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room
Image-based tracking of medical instruments is an integral part of many ...
research
∙
03/23/2020
Robust Medical Instrument Segmentation Challenge 2019
Intraoperative tracking of laparoscopic instruments is often a prerequis...
research
∙
11/05/2019
Out of distribution detection for intra-operative functional imaging
Multispectral optical imaging is becoming a key tool in the operating ro...
research
∙
10/11/2019
Methods and open-source toolkit for analyzing and visualizing challenge results
Biomedical challenges have become the de facto standard for benchmarking...
research
∙
10/09/2019
BIAS: Transparent reporting of biomedical image analysis challenges
The number of biomedical image analysis challenges organized per year is...
research
∙
07/05/2019
Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
In the medical domain, the lack of large training data sets and benchmar...
research
∙
03/08/2019
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks
Purpose: Optical imaging is evolving as a key technique for advanced sen...
research
∙
02/25/2019
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Semantic segmentation of medical images aims to associate a pixel with a...
research
∙
02/18/2019
2017 Robotic Instrument Segmentation Challenge
In mainstream computer vision and machine learning, public datasets such...
research
∙
02/15/2019
Estimation of blood oxygenation with learned spectral decoloring for quantitative photoacoustic imaging (LSD-qPAI)
One of the main applications of photoacoustic (PA) imaging is the recove...
research
∙
01/28/2019
An open-source software platform for translational photoacoustic research and its application to motion-corrected blood oxygenation estimation
Photoacoustic (PA) imaging systems based on clinical linear ultrasound a...
research
∙
08/14/2018
Analyzing Inverse Problems with Invertible Neural Networks
In many tasks, in particular in natural science, the goal is to determin...
research
∙
06/08/2018
Surgical Data Science: A Consensus Perspective
Surgical data science is a scientific discipline with the objective of i...
research
∙
06/06/2018
Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions
International challenges have become the standard for validation of biom...
research
∙
05/07/2018
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
Intraoperative segmentation and tracking of minimally invasive instrumen...
research
∙
11/27/2017
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning
Purpose: Due to the breakthrough successes of deep learning-based soluti...
research
∙
06/19/2017
Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging
Intra-operative measurements of tissue shape and multi/ hyperspectral in...
research
∙
11/25/2016
