Segmentation of anatomical structures is valuable in a variety of tasks, including 3D visualization, surgical planning, and quantitative image analysis. Manual segmentation is time-consuming and deals with intra and inter-observer variability. To develop a deep-learning approach for the fully automated segmentation of the inner ear in MRI, a 3D U-net was trained on 944 MRI scans with manually segmented inner ears as reference standard. The model was validated on an independent, multicentric dataset consisting of 177 MRI scans from three different centers. The model was also evaluated on a clinical validation set containing eight MRI scans with severe changes in the morphology of the labyrinth. The 3D U-net model showed precise Dice Similari...
This paper proposes a fully automatic method to segment the inner boundary of the bony orbit in two ...
The human ear has distinguishing features that can be used for identification. Automated ear detecti...
Background and objective: Performing patient-specific, pre-operative cochlea CT-based measurements c...
Segmentation of anatomical structures is valuable in a variety of tasks, including 3D visualization,...
Background: In-vivo MR-based high-resolution volumetric quantification methods of the endolymphatic ...
International audienceAbstract Temporal bone CT-scan is a prerequisite in most surgical procedures c...
Background In-vivo MR-based high-resolution volumetric quantification methods of the endolymphatic ...
Abstract Background Segmentation of important structures in temporal bone CT is the basis of image-g...
Background: It is difficult to characterize extracranial venous malformations (VMs) of the head and ...
We present a novel approach to automatically segment magnetic resonance (MR) images of the human bra...
118 pagesOur understanding of brain anatomy and physiology has advanced greatly thanks to the introd...
The temporal bone is a part of the lateral skull surface that contains organs responsible for hearin...
Recently, deep learning technology has been applied to medical images. This study aimed to create a ...
Skull stripping is the task of finding pixels or voxels that establishes where the brain is in amedi...
Computed tomography (CT) scans are acquired prior to cochlear implant (CI) surgery. Three-dimensiona...
This paper proposes a fully automatic method to segment the inner boundary of the bony orbit in two ...
The human ear has distinguishing features that can be used for identification. Automated ear detecti...
Background and objective: Performing patient-specific, pre-operative cochlea CT-based measurements c...
Segmentation of anatomical structures is valuable in a variety of tasks, including 3D visualization,...
Background: In-vivo MR-based high-resolution volumetric quantification methods of the endolymphatic ...
International audienceAbstract Temporal bone CT-scan is a prerequisite in most surgical procedures c...
Background In-vivo MR-based high-resolution volumetric quantification methods of the endolymphatic ...
Abstract Background Segmentation of important structures in temporal bone CT is the basis of image-g...
Background: It is difficult to characterize extracranial venous malformations (VMs) of the head and ...
We present a novel approach to automatically segment magnetic resonance (MR) images of the human bra...
118 pagesOur understanding of brain anatomy and physiology has advanced greatly thanks to the introd...
The temporal bone is a part of the lateral skull surface that contains organs responsible for hearin...
Recently, deep learning technology has been applied to medical images. This study aimed to create a ...
Skull stripping is the task of finding pixels or voxels that establishes where the brain is in amedi...
Computed tomography (CT) scans are acquired prior to cochlear implant (CI) surgery. Three-dimensiona...
This paper proposes a fully automatic method to segment the inner boundary of the bony orbit in two ...
The human ear has distinguishing features that can be used for identification. Automated ear detecti...
Background and objective: Performing patient-specific, pre-operative cochlea CT-based measurements c...