AIMC Topic: Tomography, X-Ray Computed

Clear Filters Showing 4601 to 4610 of 5128 articles

Machine learning and new insights for breast cancer diagnosis.

The Journal of international medical research
Breast cancer (BC) is the most prominent form of cancer among females all over the world. The current methods of BC detection include X-ray mammography, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography and bre...

Deep learning in the radiologic diagnosis of osteoporosis: a literature review.

The Journal of international medical research
OBJECTIVE: Osteoporosis is a systemic bone disease characterized by low bone mass, damaged bone microstructure, increased bone fragility, and susceptibility to fractures. With the rapid development of artificial intelligence, a series of studies have...

Automatic pterygopalatine fossa segmentation and localisation based on DenseASPP.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Allergic rhinitis constitutes a widespread health concern, with traditional treatments often proving to be painful and ineffective. Acupuncture targeting the pterygopalatine fossa proves effective but is complicated due to the intricate n...

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Radiology
Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improv...

Artificial intelligence in lung cancer screening: Detection, classification, prediction, and prognosis.

Cancer medicine
BACKGROUND: The exceptional capabilities of artificial intelligence (AI) in extracting image information and processing complex models have led to its recognition across various medical fields. With the continuous evolution of AI technologies based o...

[Identifying Novel Coronavirus Pneumonia With CT Images: A Deep Learning Approach With Detail Upsampling and Attention Guidance].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local infor...

A systematic review on deep learning-based automated cancer diagnosis models.

Journal of cellular and molecular medicine
Deep learning is gaining importance due to its wide range of applications. Many researchers have utilized deep learning (DL) models for the automated diagnosis of cancer patients. This paper provides a systematic review of DL models for automated dia...

Denoising Multiphase Functional Cardiac CT Angiography Using Deep Learning and Synthetic Data.

Radiology. Artificial intelligence
Coronary CT angiography is increasingly used for cardiac diagnosis. Dose modulation techniques can reduce radiation dose, but resulting functional images are noisy and challenging for functional analysis. This retrospective study describes and evalua...