141 citations · 406 across the 66 of their papers we have counts for
7 papers · 1 filter
An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
Kelly Payette, Priscille de Dumast, Hamza Kebiri +17
It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders.…
Cranial Implant Prediction using Low-Resolution 3D Shape Completion and High-Resolution 2D Refinement
Amirhossein Bayat, Suprosanna Shit, Adrian Kilian +3
Designing of a cranial implant needs a 3D understanding of the complete skull shape. Thus, taking a 2D approach is sub-optimal, since a 2D model lacks a holistic 3D view of both th…
Geometry-aware neural solver for fast Bayesian calibration of brain tumor models
Ivan Ezhov, Tudor Mot, Suprosanna Shit +9
Modeling of brain tumor dynamics has the potential to advance therapeutic planning. Current modeling approaches resort to numerical solvers that simulate the tumor progression acco…
Automated Claustrum Segmentation in Human Brain MRI Using Deep Learning
Hongwei Li, Aurore Menegaux, Benita Schmitz-Koep +6
In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function. However, relatively few in…
A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images
Stefan Gerl, Johannes C. Paetzold, Hailong He +7
Raster-scan optoacoustic mesoscopy (RSOM) is a powerful, non-invasive optical imaging technique for functional, anatomical, and molecular skin and tissue analysis. However, both th…
Red-GAN: Attacking class imbalance via conditioned generation. Yet another perspective on medical image synthesis for skin lesion dermoscopy and brain tumor MRI
Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit +7
Exploiting learning algorithms under scarce data regimes is a limitation and a reality of the medical imaging field. In an attempt to mitigate the problem, we propose a data augmen…
clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
Suprosanna Shit, Johannes C. Paetzold, Anjany Sekuboyina +6
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, the topology is their mo…