A review of deep learning ct reconstruction from incomplete projection data
Computed tomography (CT) is a widely used imaging technique in both medical and
industrial applications. However, accurate CT reconstruction requires complete projection …
industrial applications. However, accurate CT reconstruction requires complete projection …
[HTML][HTML] Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report
Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of
radiation to tumors while sparing healthy tissues over multiple days. Computed tomography …
radiation to tumors while sparing healthy tissues over multiple days. Computed tomography …
Computer-assisted preoperative planning of bone fracture fixation surgery: A state-of-the-art review
Background: Bone fracture fixation surgery is one of the most commonly performed surgical
procedures in the orthopedic field. However, fracture healing complications occur frequently …
procedures in the orthopedic field. However, fracture healing complications occur frequently …
InDuDoNet: An interpretable dual domain network for CT metal artifact reduction
For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods
have achieved promising performances, most of them suffer from two problems: 1) the CT …
have achieved promising performances, most of them suffer from two problems: 1) the CT …
DICDNet: deep interpretable convolutional dictionary network for metal artifact reduction in CT images
Computed tomography (CT) images are often impaired by unfavorable artifacts caused by
metallic implants within patients, which would adversely affect the subsequent clinical …
metallic implants within patients, which would adversely affect the subsequent clinical …
DiffuX2CT: Diffusion Learning to Reconstruct CT Images from Biplanar X-Rays
Computed tomography (CT) is widely utilized in clinical settings because it delivers detailed
3D images of the human body. However, performing CT scans is not always feasible due to …
3D images of the human body. However, performing CT scans is not always feasible due to …
Towards unifying anatomy segmentation: automated generation of a full-body CT dataset via knowledge aggregation and anatomical guidelines
In this study, we present a method for generating automated anatomy segmentation datasets
using a sequential process that involves nnU-Net-based pseudo-labeling and anatomy …
using a sequential process that involves nnU-Net-based pseudo-labeling and anatomy …
A bidirectional framework for fracture simulation and deformation-based restoration prediction in pelvic fracture surgical planning
Pelvic fracture is a severe trauma with life-threatening implications. Surgical reduction is
essential for restoring the anatomical structure and functional integrity of the pelvis, requiring …
essential for restoring the anatomical structure and functional integrity of the pelvis, requiring …
Segmentation of the iliac crest from CT-data for virtual surgical planning of facial reconstruction surgery using deep learning
S Raith, T Pankert, J de Souza Nascimento… - Scientific Reports, 2025 - nature.com
Background and objectives: For the planning of surgical procedures involving the bony
reconstruction of the mandible, the autologous iliac crest graft, along with the fibula graft, has …
reconstruction of the mandible, the autologous iliac crest graft, along with the fibula graft, has …
Foundation model for advancing healthcare: Challenges, opportunities, and future directions
Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …