Lung cancer has one of the highest mortalities of all cancers. According to the National Lung
Screening Trial, patients who underwent low-dose computed tomography (CT) scanning …

Computer-aided detection or diagnosis (CAD) has been a promising area of research over
the last two decades. Medical image analysis aims to provide a more efficient diagnostic and …

The aim of this study was to provide an overview of the literature available on machine
learning (ML) algorithms applied to the Lung Image Database Consortium Image Collection …

Lung Cancer is the most fast growing cancer around the world and is mostly diagnosed at
an advanced stage. Due to enhancement in medical imaging modalities like Computed …

Background Accurately detecting and examining lung nodules early is key in diagnosing
lung cancers and thus one of the best ways to prevent lung cancer deaths. Radiologists …

Purpose This study suggests a lifelong learning‐based convolutional neural network (LL‐
CNN) algorithm as a superior alternative to single‐task learning approaches for automatic …

Purpose Medical image segmentation is the most widely used technique in diagnostic and
clinical research. However, accurate segmentation of target organs from blurred border …

Early diagnosis of lung cancer is very important in improving patients life expectancies. Due
to the high number of Computed Tomography (CT) images, fast and accurate diagnosis is …

It is critical to have accurate detection of lung nodules in CT images for the early diagnosis of
lung cancer. In order to achieve this, it is necessary to reduce the false positive rate of …

Lung cancer poses a significant threat, contributing significantly to cancer-related mortality.
Computer-aided detection plays a pivotal role, particularly in the automated identification of …