In this paper, we present a new representation model for the topology and the geometry of a 3D segmented image. This model has been designed to provide main ...
Mar 27, 2022 · In this paper, we propose a deep learning-based approach that uses global and local features which are of importance in the medical image segmentation process.
Segmentation of MRI head anatomy using deep volumetric networks ...
www.ncbi.nlm.nih.gov › PMC8209627
After the entire image has been segmented, a 3D CRF processes the resulting output segmentation while taking the original input image into account (green arrow) ...
Mar 24, 2024 · In this paper, we present a comprehensive methodology focusing on streamlining the segmentation, reconstruction, and visualization process of 3D MRI data.
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Aug 8, 2024 · This work introduces a novel approach towards creating 3-dimensional (3D) medical foundation models for multimodal neuroimage segmentation through self- ...
Aug 5, 2024 · In this paper, we explore the zero-shot capabilities of SAM 2, the next-generation Meta SAM model trained on videos, for 3D medical image segmentation.
In this paper an image-based method founded on mathematical morphology is presented in order to facilitate the segmentation of cerebral structures over ...
The current systematic review aims to present the common bottlenecks for musculoskeletal structures analysis (eg, small sample size, data inhomogeneity)
3D Deep Learning for Anatomical Structure Segmentation in Multiple ...
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This paper presents a novel computing approach for automated organ and muscle segmentation in medical images from multiple modalities
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