4 papers
Flow Matching Meets 3D Curvilinear Structure Segmentation in Medical Imaging
Sidi Mohamed Sid'El Moctar, Nicolas Vitry, Hélène Bouvrais
Segmentation of curvilinear anatomical structures in 3D medical images remains challenging due to complex topology, severe class imbalance, weak contrast, and large variations in s…
CurvSegFlow: Time-Conditioned Flow Matching for Robust Segmentation of Curvilinear Structures in Noisy Biomedical Images
Sidi Mohamed Sid'El Moctar, Achraf Ait Laydi, Alexandre Beber +4
Accurate segmentation of curvilinear structures remains challenging in biomedical imaging due to their thin geometry, complex topology, and sensitivity to noise. This is particular…
MTCurv: Deep learning for direct microtubule curvature mapping in noisy fluorescence microscopy images
Achraf Ait Laydi, Sidi Mohamed Sid'El Moctar, Yousef El Mourabit +1
Accurate quantification of the geometry of curvilinear biological structures is essential for understanding cellular mechanics and disease-related morphological alterations. Microt…
MTFlow: Time-Conditioned Flow Matching for Microtubule Segmentation in Noisy Microscopy Images
Sidi Mohamed Sid El Moctar, Achraf Ait Laydi, Yousef El Mourabit +1
Microtubules are cytoskeletal filaments that play essential roles in many cellular processes and are key therapeutic targets in several diseases. Accurate segmentation of microtubu…