1.4k citations · 3.4k across the 30 of their papers we have counts for
13 papers · 1 filter
Benchmarking Foundation Models for Renal Lesion Stratification in CT
Hartmut Häntze, Sarah de Boer, Myrthe Buser +7
The rapid proliferation of open-source medical foundation models (FMs) raises a practical question: how well do their pre-trained representations transfer to clinically relevant bu…
Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Framework
Sarah de Boer, Hartmut Häntze, Kiran Vaidhya Venkadesh +9
Renal mass segmentation has important potential to enhance the clinical workflow, especially in settings requiring quantitative assessments. Kidney volume could serve as an importa…
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…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Robust Segmentation Models using an Uncertainty Slice Sampling Based Annotation Workflow
Grzegorz Chlebus, Andrea Schenk, Horst K. Hahn +2
Semantic segmentation neural networks require pixel-level annotations in large quantities to achieve a good performance. In the medical domain, such annotations are expensive, beca…
Iterative Augmentation of Visual Evidence for Weakly-Supervised Lesion Localization in Deep Interpretability Frameworks: Application to Color Fundus Images
Cristina González-Gonzalo, Bart Liefers, Bram van Ginneken +1
Interpretability of deep learning (DL) systems is gaining attention in medical imaging to increase experts' trust in the obtained predictions and facilitate their integration in cl…
Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration
Cristina González-Gonzalo, Verónica Sánchez-Gutiérrez, Paula Hernández-Martínez +5
Purpose: To validate the performance of a commercially-available, CE-certified deep learning (DL) system, RetCAD v.1.3.0 (Thirona, Nijmegen, The Netherlands), for the joint automat…
Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions
Nikolas Lessmann, Bram van Ginneken, Majd Zreik +4
Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable qua…
Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images
Péter Bándi, Rob van de Loo, Milad Intezar +5
Tissue segmentation is an important pre-requisite for efficient and accurate diagnostics in digital pathology. However, it is well known that whole-slide scanners can fail in detec…
The importance of stain normalization in colorectal tissue classification with convolutional networks
Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi +6
The development of reliable imaging biomarkers for the analysis of colorectal cancer (CRC) in hematoxylin and eosin (H&E) stained histopathology images requires an accurate and rep…
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge
Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas de Bel +29
Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few…
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +8
Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel d…
Towards automatic pulmonary nodule management in lung cancer screening with deep learning
Francesco Ciompi, Kaman Chung, Sarah J. van Riel +10
The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decid…