MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research

Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data
Med Image Comput Comput Assist Interv. 2022 Sep;13431:113-122. doi: 10.1007/978-3-031-16431-6_11. Epub 2022 Sep 15.ABSTRACTAdvanced contemporary diffusion models for tissue microstructure often require diffusion MRI (DMRI) data with sufficiently dense sampling in the diffusion wavevector space for reliable model fitting, which might not always be feasible in practice. A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely sampled data. However, existing methods are either agnostic to the data geometry in the diffusion wavevector space ...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Geng Chen Haotian Jiang Jiannan Liu Jiquan Ma Hui Cui Yong Xia Pew-Thian Yap Source Type: research

Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations
Med Image Comput Comput Assist Interv. 2022 Sep;13435:549-559. doi: 10.1007/978-3-031-16443-9_53. Epub 2022 Sep 16.ABSTRACTSmall bowel path tracking is a challenging problem considering its many folds and contact along its course. For the same reason, it is very costly to achieve the ground-truth (GT) path of the small bowel in 3D. In this work, we propose to train a deep reinforcement learning tracker using datasets with different types of annotations. Specifically, we utilize CT scans that have only GT small bowel segmentation as well as ones with the GT path. It is enabled by designing a unique environment that is compa...
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - May 1, 2023 Category: Radiology Authors: Seung Yeon Shin Ronald M Summers Source Type: research