CT scan pancreatic cancer segmentation and classification using deep learning and the tunicate swarm algorithm.

ABSTRACT: Pancreatic cancer (PC) is a very lethal disease with a low survival rate, making timely and accurate diagnoses critical for successful treatment. PC classification in computed tomography (CT) scans is a vital task that aims to accurately discriminate between tumorous and non-tumorous pancreatic tissues. CT images provide detailed cross-sectional images of the pancreas, which allows oncologists and radiologists to analyse the characteristics and morphology of the tissue. Machine learning (ML) approaches, together with deep learning (DL) algorithms, are commonly explored to improve and automate the performance of PC classification in CT scans. DL algorithms, particularly convolutional neural networks (CNNs), are broadly utilized for medical image analysis tasks, involving segmentation and cl

SUBMITTER: Gandikota HP 

PROVIDER: S-EPMC10627451 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature