A hybrid deep learning model for effective segmentation and classification of lung nodules from CT images
M Murugesan, K Kaliannan, S Balraj… - Journal of Intelligent …, 2022 - content.iospress.com
Deep learning algorithms will be used to detect lung nodule anomalies at an earlier stage.
The primary goal of this effort is to properly identify lung cancer, which is critical in …
The primary goal of this effort is to properly identify lung cancer, which is critical in …
Graph neural network (GNN) in image and video understanding using deep learning for computer vision applications
P Pradhyumna, GP Shreya - 2021 Second International …, 2021 - ieeexplore.ieee.org
Graph neural networks (GNNs) is an information-processing system that uses message
passing among graph nodes. In recent years, GNN variants including graph attention …
passing among graph nodes. In recent years, GNN variants including graph attention …
Transfer learning based breast cancer classification using one-hot encoding technique
Early diagnosis of breast cancer can be curable with precise techniques and improve
patients prognosis with cancer. Most people failed to detect cancer early, leading to an …
patients prognosis with cancer. Most people failed to detect cancer early, leading to an …
Optimized deep learning model for lung cancer prediction using ANN algorithm
Cancer is disease in which there is unnatural growth of abnormal cells that infest healthy
cells in the body. Lung cancer invokes imbalance in cells which affects the lungs. Prediction …
cells in the body. Lung cancer invokes imbalance in cells which affects the lungs. Prediction …
A comprehensive review of Lung nodule identification using an effective Computer-Aided Diagnosis (CAD) System
NA Pande, D Bhoyar - 2022 4th International Conference on …, 2022 - ieeexplore.ieee.org
Lung cancer is a nothing but abnormal swelling of lung tissues and could be a life
threatening one. As per statistics, it is responsible for more deaths than any other type of …
threatening one. As per statistics, it is responsible for more deaths than any other type of …
[HTML][HTML] Dilated dendritic learning of global–local feature representation for medical image segmentation
Medical image segmentation serves as an important tool in the treatment of various medical
diseases. However, achieving precise and efficient segmentation remains challenging due …
diseases. However, achieving precise and efficient segmentation remains challenging due …
Lung cancer segmentation from CT scan images using modified mayfly optimization and particle swarm optimization algorithm
The development of a computer-aided detection system is a critical component of clinical
decision-making As the death rate grows, cancer has become a major concern for both men …
decision-making As the death rate grows, cancer has become a major concern for both men …
Ensemble deep learning models for lung cancer diagnosis in histopathological images
J Bokefode, MVP Rao, G Komarasamy - Procedia Computer Science, 2022 - Elsevier
Computed Tomography, widely known as CT scan, is used for the detection of lung cancers.
However, sometimes doctors cannot detect such harmful diseases based on the CT scan …
However, sometimes doctors cannot detect such harmful diseases based on the CT scan …
Predictive Model for COVID-19 Using Deep Learning
H Goyal, D Attri, G Aggarwal, A Bhatt - Pervasive Computing and Social …, 2022 - Springer
The Coronavirus has now taken more than 2.4 million lives and infected more than 100.2
million people. The spread of Coronavirus has had an adverse effect on global health and …
million people. The spread of Coronavirus has had an adverse effect on global health and …
Improved graph neural network-based green anaconda optimization for segmenting and classifying the lung cancer.
Normal lung cells incur genetic damage over time, which causes unchecked cell growth and
ultimately leads to lung cancer. Nearly 85% of lung cancer cases are caused by smoking …
ultimately leads to lung cancer. Nearly 85% of lung cancer cases are caused by smoking …