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 a common type of cancer that requires early diagnosis due to its often fatal
consequences. Computer image processing techniques may be useful to increase the …

Computer aided detection system was developed to identify the pulmonary nodules to
diagnose the cancer cells. Main aim of this research enables an automated image analysis …

The three-dimensional analysis on lung computed tomography scan was carried out in this
study to detect the malignant lung nodules. An automatic three-dimensional segmentation …

A quantitative model is developed in this work to predict the lung nodules which have the
potential to grow in future. An Auto Cluster Seed K-means Morphological segmentation …

Early detection of lung cancer is of vital importance to successful treatment where Computed
Tomography (CT) screening are considered one of the best methods for detection the early …

Malignant nodules may be due to primary tumors or a metastasis and, given the importance
of diagnosing early primary lung tumors, the detection of pulmonary nodules is critical …

Background Accurate segmentation of pulmonary nodules on computed tomography (CT)
scans plays a crucial role in the evaluation and management of patients with suspicion of …

Lung cancer is one of the deadliest cancers all over the world. One of the indications of lung
cancers is the presence of the lung nodules which can appear individually or attached to the …

An effective fuzzy auto-seed cluster means morphological algorithm developed in this work
to segment the lung nodules from the consecutive slices of Computer Tomography (CT) …