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20092026
most citedTotalSegmentator: robust segmentation of 104 anatomical structures in CT images

1.5k citations

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11 papers · 1 filter

eess.IV2025★ 1 cited

In search of truth: Evaluating concordance of AI-based anatomy segmentation models

Lena Giebeler, Deepa Krishnaswamy, David Clunie +9

Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the cha…

eess.IV2024★ 98 cited

TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI

Tugba Akinci D'Antonoli, Lucas K. Berger, Ashraya K. Indrakanti +16

Since the introduction of TotalSegmentator CT, there is demand for a similar robust automated MRI segmentation tool that can be applied across all MRI sequences and anatomic struct…

eess.IV2024★ 97 cited

DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images

Michael Götz, Christian Weber, Franciszek Binczyk +7

We propose a new method that employs transfer learning techniques to effectively correct sampling selection errors introduced by sparse annotations during supervised learning for a…

eess.IV2023★ 30 cited

Towards contrast-agnostic soft segmentation of the spinal cord

Sandrine Bédard, Enamundram Naga Karthik, Charidimos Tsagkas +5

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and monitoring of cord compression or neurod…

eess.IV2023★ 19 cited

Point Cloud Diffusion Models for Automatic Implant Generation

Paul Friedrich, Julia Wolleb, Florentin Bieder +2

Advances in 3D printing of biocompatible materials make patient-specific implants increasingly popular. The design of these implants is, however, still a tedious and largely manual…

eess.IV2023★ 6 cited

Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation

Francesco Santini, Jakob Wasserthal, Abramo Agosti +11

Purpose: To present and evaluate Dafne (deep anatomical federated network), a freely available decentralized, collaborative deep learning system for the semantic segmentation of ra…

eess.IV2022★ 6 cited

Novel structural-scale uncertainty measures and error retention curves: application to multiple sclerosis

Nataliia Molchanova, Vatsal Raina, Andrey Malinin +6

This paper focuses on the uncertainty estimation for white matter lesions (WML) segmentation in magnetic resonance imaging (MRI). On one side, voxel-scale segmentation errors cause…

eess.IV2022★ 1.5k cited

TotalSegmentator: robust segmentation of 104 anatomical structures in CT images

Jakob Wasserthal, Hanns-Christian Breit, Manfred T. Meyer +9

We present a deep learning segmentation model that can automatically and robustly segment all major anatomical structures in body CT images. In this retrospective study, 1204 CT ex…

eess.IV2020★ 9 cited

Appearance Learning for Image-based Motion Estimation in Tomography

Alexander Preuhs, Michael Manhart, Philipp Roser +5

In tomographic imaging, anatomical structures are reconstructed by applying a pseudo-inverse forward model to acquired signals. Geometric information within this process is usually…

eess.IV2020★ 156 cited

Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT

Shikha Chaganti, Abishek Balachandran, Guillaume Chabin +17

Purpose: To present a method that automatically segments and quantifies abnormal CT patterns commonly present in coronavirus disease 2019 (COVID-19), namely ground glass opacities…

eess.IV2019★ 92 cited

Magnetization Transfer in Magnetic Resonance Fingerprinting

Tom Hilbert, Ding Xia, Kai Tobias Block +5

Purpose: To study the effects of magnetization transfer (MT, in which a semisolid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF)…