Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

Given the increased interest in utilizing artificial intelligence as an assistive tool in the
medical sector, colorectal polyp detection and classification using deep learning techniques …

In the realm of computer vision, semantic segmentation is the task of recognizing objects in
images at the pixel level. This is done by performing a classification of each pixel. The task is …

Despite the successful demonstration of the deep learning architectures for Automatic
Colonoscopy Polyp Detection (ACPD), studies have argued upon human bias, and lack of …

Background and Aims Publicly available databases containing colonoscopic imaging data
are valuable resources for artificial intelligence (AI) research. Currently, little is known …

Colorectal cancer (CRC) is one of the most lethal kinds of cancer, so early detection is
critical. Three datasets, namely CNN transfer learning with discrete wavelet transform …

Deep Learning has contributed significantly to the advances made in the fields of Medical
Imaging and Computer Aided Diagnosis (CAD). Although a variety of Deep Learning (DL) …

Recently, compressive sensing (CS) schemes have been studied as a new compression
modality that exploits the sensing matrix in the measurement scheme and the reconstruction …

Colorectal cancer (CRC) is a common digestive system tumor with high morbidity and
mortality worldwide. At present, the use of computer-assisted colonoscopy technology to …

Coronal anatomic slices of structural MRI images clearly show the topographical structures
of the Hippocampus and Amygdala, which are essential for early diagnosis of Alzheimer's …