M&M: Unsupervised Mamba-based Mastoidectomy for Cochlear Implant Surgery with Noisy Data

Autor: Zhang, Yike, Davalos, Eduardo, Su, Dingjie, Lou, Ange, Noble, Jack H.

Cochlear Implant (CI) procedures involve inserting an array of electrodes into the cochlea located inside the inner ear. Mastoidectomy is a surgical procedure that uses a high-speed drill to remove part of the mastoid region of the temporal bone, pro

Externí odkaz: http://arxiv.org/abs/2407.15787

Unsupervised Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation via Semi-supervised Learning and Label Fusion

Autor: Liu, Han, Fan, Yubo, Cui, Can, Su, Dingjie, McNeil, Andrew, Dawant, Benoit M.

Automatic methods to segment the vestibular schwannoma (VS) tumors and the cochlea from magnetic resonance imaging (MRI) are critical to VS treatment planning. Although supervised methods have achieved satisfactory performance in VS segmentation, the

Externí odkaz: http://arxiv.org/abs/2201.10647

Atlas-Based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks

Autor: Wang, Jianing, Su, Dingjie, Fan, Yubo, Chakravorti, Srijata, Noble, Jack H., Dawant, Benoit M.

We propose an atlas-based method to segment the intracochlear anatomy (ICA) in the post-implantation CT (Post-CT) images of cochlear implant (CI) recipients that preserves the point-to-point correspondence between the meshes in the atlas and the segm

Externí odkaz: http://arxiv.org/abs/2107.03987

Automatic, deep-learning-based segmentation of the amygdalohippocampectomy resection cavity in MR images.

Autor: Su, Dingjie, Paulo, Danika L., Ball, Tyler, Morgan, Victoria L., Englot, Dario J., Dawant, Benoit M.

Publikováno v: Proceedings of SPIE; 3/10/2023, Vol. 12466, p1246610-1246610, 1p

Atlas-based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks.

Autor: Wang J; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA., Su D; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA., Fan Y; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA., Chakravorti S; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA., Noble JH; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA., Dawant BM; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA.

Publikováno v: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention [Med Image Comput Comput Assist Interv] 2021 Sep-Oct; Vol. 12904, pp. 14-23. Date of Electronic Publication: 2021 Sep 21.