Medical imaging is a rich source of invaluable information necessary for clinical judgements.
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …

At present, computed tomography (CT) is widely used to assist disease diagnosis.
Especially, computer aided diagnosis (CAD) based on artificial intelligence (AI) recently …

Many research applications of neuroimaging use magnetic resonance imaging (MRI). As
such, recommendations for image analysis and standardized imaging pipelines exist …

A three-dimensional (3-D) convolutional neural network (CNN) trained from scratch is
presented for the classification of pulmonary nodule malignancy from low-dose chest CT …

Purpose To develop a deep learning model that segments intracranial structures on head
CT scans. Materials and Methods In this retrospective study, a primary dataset containing 62 …

Background Head computed tomography (CT) with perfusion imaging has become crucial in
the selection of patients for mechanical thrombectomy. In recent years, machine learning …

Computer tomography is an extensively used method for the detection of the disease in the
subjects. Basically, computer‐aided tomography depending on the artificial intelligence …

Computed Tomography (CT) is the first choice of imaging modality for different acute clinical
conditions28–30. CT is widely available and is a cheaper and faster imaging method with …

Image retrieval with traditional relevance feedback encounters problems:(1) ability to
represent handcrafted features which is limited, and (2) inefficient with high-dimensional …

Pattern-recognition algorithms from the domain of machine learning play a prominent role in
embedded sensing systems, in order to derive inferences from sensor data. Very often, such …