The study's primary objectives encompass the following: (i) To implement the object detection of ovarian follicles using you only look once (YOLO)v8 and subsequently segment the identified follicles using a hybrid fuzzy c-means-based active contour t...
PURPOSE: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of OCT images.
OBJECTIVES: This study aimed to train a 3D U-Net convolutional neural network (CNN) for mandible and lower dentition segmentation from cone-beam computed tomography (CBCT) scans.
Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dose-volume histogram of prostatic urethra has been associated with such toxicities in previous reports. Previous research has focused on estimating the ...
BACKGROUND: Adequate professional preparation of nursing undergraduates is conducive to developing health care careers. Deep learning is important for enhancing nursing competencies and the overall quality of students. However, limited research has b...
Critical reviews in oncology/hematology
Aug 14, 2024
Radiomics, analysing quantitative features from medical imaging, has rapidly become an emerging field in translational oncology. Radiomics has been investigated in several neoplastic malignancies as it might allow for a non-invasive tumour characteri...
OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essent...
Myocarditis, marked by heart muscle inflammation, poses significant clinical challenges. This study, guided by PRISMA guidelines, explores the expanding role of artificial intelligence (AI) in myocarditis, aiming to consolidate current knowledge and ...
The advent of computer vision technology and increased usage of video cameras in clinical settings have facilitated advancements in movement disorder analysis. This review investigated these advancements in terms of providing practical, low-cost solu...
The increasing availability of biomedical data creates valuable resources for developing new deep learning algorithms to support experts, especially in domains where collecting large volumes of annotated data is not trivial. Biomedical data include s...
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