AIMC Topic: Tomography, X-Ray Computed
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Task based evaluation of sparse view CT reconstruction techniques for intracranial hemorrhage diagnosis using an AI observer model.
Scientific reports
Jul 17, 2025
Sparse-view computed tomography (CT) holds promise for reducing radiation exposure and enabling novel system designs. Traditional reconstruction algorithms, including Filtered Backprojection (FBP) and Model-Based Iterative Reconstruction (MBIR), ofte...
FSS-ULivR: a clinically-inspired few-shot segmentation framework for liver imaging using unified representations and attention mechanisms.
Journal of cancer research and clinical oncology
Jul 17, 2025
Precise liver segmentation is critical for accurate diagnosis and effective treatment planning, serving as a foundation for medical image analysis. However, existing methods struggle with limited labeled data, poor generalizability, and insufficient ...
Conditional GAN performs better than orthopedic surgeon in virtual reduction of femoral neck fracture.
BMC musculoskeletal disorders
Jul 16, 2025
OBJECTIVE: Satisfied reduction of fracture is hard to achieve. The purpose of this study is to develop a virtual fracture reduction technique using conditional GAN (Generative Adversarial Network), and evaluate its performance in simulating and guidi...
An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data.
BMC cancer
Jul 16, 2025
BACKGROUND: The accurate early-stage diagnosis of gallbladder cancer (GBC) is regarded as one of the major challenges in the field of oncology. However, few studies have focused on the comprehensive classification of GBC based on multiple modalities....
Image quality and radiation dose of reduced-dose abdominopelvic computed tomography (CT) with silver filter and deep learning reconstruction.
Scientific reports
Jul 16, 2025
To assess the image quality and radiation dose between reduced-dose CT with deep learning reconstruction (DLR) using SilverBeam filter and standard dose with iterative reconstruction (IR) in abdominopelvic CT. In total, 182 patients (mean age ± stand...
ComptoNet: a Compton-map guided deep learning framework for multi-scatter estimation in multi-source stationary CT.
Physics in medicine and biology
Jul 16, 2025
Multi-source stationary computed tomography (MSS-CT) offers significant advantages in medical and industrial applications due to its gantryless scan architecture and capability of simultaneous multi-source emission. However, the lack of anti-scatter ...
Non-invasive liver fibrosis screening on CT images using radiomics.
BMC medical imaging
Jul 15, 2025
PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of the liver.
An efficient deep learning based approach for automated identification of cervical vertebrae fracture as a clinical support aid.
Scientific reports
Jul 15, 2025
Cervical vertebrae fractures pose a significant risk to a patient's health. The accurate diagnosis and prompt treatment need to be provided for effective treatment. Moreover, the automated analysis of the cervical vertebrae fracture is of utmost impo...
Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.
Scientific reports
Jul 15, 2025
To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of venous phase using deep learning (DL) and Radiomics approaches to predict lymphovascular invasion in gastric cancer prior to surgery. We retrospectiv...
A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study.
World journal of emergency surgery : WJES
Jul 14, 2025
BACKGROUND: Accurately identifying difficult laparoscopic cholecystectomy (DLC) preoperatively remains a clinical challenge. Previous studies utilizing clinical variables or morphological imaging markers have demonstrated suboptimal predictive perfor...
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