A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques
This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
Self-supervised transfer learning framework driven by visual attention for benign–malignant lung nodule classification on chest CT
Lung cancer is one of the most fatal malignant diseases, which poses an acute menace to
human health and life. The accurate differential diagnosis of lung nodules is a vital step in …
human health and life. The accurate differential diagnosis of lung nodules is a vital step in …
[HTML][HTML] Beyond supervised: The rise of self-supervised learning in autonomous systems
H Taherdoost - Information, 2024 - mdpi.com
Supervised learning has been the cornerstone of many successful medical imaging
applications. However, its reliance on large labeled datasets poses significant challenges …
applications. However, its reliance on large labeled datasets poses significant challenges …
Effective lung nodule detection using deep CNN with dual attention mechanisms
Z UrRehman, Y Qiang, L Wang, Y Shi, Q Yang… - Scientific Reports, 2024 - nature.com
Novel methods are required to enhance lung cancer detection, which has overtaken other
cancer-related causes of death as the major cause of cancer-related mortality. Radiologists …
cancer-related causes of death as the major cause of cancer-related mortality. Radiologists …
[HTML][HTML] MITER: Medical Image–TExt joint adaptive pretRaining with multi-level contrastive learning
Recently multimodal medical pretraining models play a significant role in automatic medical
image and text analysis that has wide social and economical impact in healthcare. Despite …
image and text analysis that has wide social and economical impact in healthcare. Despite …
A novel benign and malignant classification model for lung nodules based on multi-scale interleaved fusion integrated network
E Lv, X Kang, P Wen, J Tian, M Zhang - Scientific Reports, 2024 - nature.com
One of the precursors of lung cancer is the presence of lung nodules, and accurate
identification of their benign or malignant nature is important for the long-term survival of …
identification of their benign or malignant nature is important for the long-term survival of …
Ensemble framework based on attributes and deep features for benign-malignant classification of lung nodule
J Qiao, Y Fan, M Zhang, K Fang, D Li… - … Signal Processing and …, 2023 - Elsevier
Early detection and identification of malignant lung nodules improve the survival of lung
cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung …
cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung …
Self-supervised learning framework application for medical image analysis: a review and summary
Manual annotation of medical image datasets is labor-intensive and prone to biases.
Moreover, the rate at which image data accumulates significantly outpaces the speed of …
Moreover, the rate at which image data accumulates significantly outpaces the speed of …
Automatic classification of pulmonary nodules in computed tomography images using pre-trained networks and bag of features
Lung cancer has the highest incidence in the world. The standard tests for its diagnostics are
medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of …
medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of …