Journal of cancer research and clinical oncology
Feb 3, 2025
OBJECTIVE: The objective of this study is to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model. This approach is intended to address the limitations of manual segmentation, which is known to...
BACKGROUND: Sparse-view CT shortens scan time and reduces radiation dose but results in severe streak artifacts due to insufficient sampling data. Deep learning methods can now suppress these artifacts and improve image quality in sparse-view CT reco...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Feb 2, 2025
PURPOSE: This study aimed to develop a deep-learning framework to generate multi-organ masks from CT images in adult and pediatric patients.
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2025
Automated classification of liver lesions in multi-phase CT and MR scans is of clinical significance but challenging. This study proposes a novel Siamese Dual-Resolution Transformer (SDR-Former) framework, specifically designed for liver lesion class...
International journal of surgery (London, England)
Feb 1, 2025
BACKGROUND: Early recurrence in patients with locally advanced gastric cancer (LAGC) portends aggressive biological characteristics and a dismal prognosis. Predicting early recurrence may help determine treatment strategies for LAGC. The goal is to d...
Computer methods and programs in biomedicine
Jan 31, 2025
PURPOSE: In medical deep learning, models not trained from scratch are typically fine-tuned based on ImageNet-pretrained models. We posit that pretraining on data from the domain of the downstream task should almost always be preferable.
International journal of medical informatics
Jan 30, 2025
BACKGROUND: With advancements in medical technology and science, chronic obstructive pulmonary disease (COPD), one of the world's three major chronic diseases, has seen numerous remarkable outcomes when combined with artificial intelligence, particul...
The purpose of this study was to investigate the utility of neural networks to estimate the hip joint center location in sheep and compare the accuracy of neural networks to previously developed linear regression models. CT scans from 16 sheep of var...
OBJECTIVES: To evaluate the efficiency of super-resolution deep-learning reconstruction (SR-DLR) optimized for helical body imaging in assessing pancreatic ductal adenocarcinoma (PDAC) using normal-resolution (NR) CT scanner.