Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
[HTML][HTML] Lung nodule diagnosis and cancer histology classification from computed tomography data by convolutional neural networks: A survey
Lung cancer is among the deadliest cancers. Besides lung nodule classification and
diagnosis, developing non-invasive systems to classify lung cancer histological …
diagnosis, developing non-invasive systems to classify lung cancer histological …
Self-supervised transfer learning based on domain adaptation for benign-malignant lung nodule classification on thoracic CT
H Huang, R Wu, Y Li, C Peng - IEEE Journal of Biomedical and …, 2022 - ieeexplore.ieee.org
The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung
cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule …
cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule …
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 …
Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …
routines provide unquestionable benefits in connecting human medical expertise with …
Benchmarking multi-task learning for sentiment analysis and offensive language identification in under-resourced dravidian languages
To obtain extensive annotated data for under-resourced languages is challenging, so in this
research, we have investigated whether it is beneficial to train models using multi-task …
research, we have investigated whether it is beneficial to train models using multi-task …
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 …
Pulmonary nodule classification using feature and ensemble learning-based fusion techniques
The Pulmonary nodule indicates the presence of lung cancer. The deep convolutional
neural networks (DCNNs) have been widely used to classify the pulmonary nodule as …
neural networks (DCNNs) have been widely used to classify the pulmonary nodule as …
Pulmonary nodule detection using 3-d residual u-net oriented context-guided attention and multi-branch classification network
H Yuan, Y Wu, J Cheng, Z Fan, Z Zeng - Ieee Access, 2021 - ieeexplore.ieee.org
Accurate detection of pulmonary nodules on chest computed tomography scans is crucial to
early diagnosis of lung cancer. To address the thorn problems on low detection sensitivity …
early diagnosis of lung cancer. To address the thorn problems on low detection sensitivity …
Reconstruction-assisted feature encoding network for histologic subtype classification of non-small cell lung cancer
H Li, Q Song, D Gui, M Wang, X Min… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Accurate histological subtype classification between adenocarcinoma (ADC) and squamous
cell carcinoma (SCC) using computed tomography (CT) images is of great importance to …
cell carcinoma (SCC) using computed tomography (CT) images is of great importance to …