Machine learning and vision transformers for thyroid carcinoma diagnosis: A review
The growing interest in developing smart diagnostic systems to help medical experts
process extensive data for treating incurable diseases has been notable. In particular, the …
process extensive data for treating incurable diseases has been notable. In particular, the …
MLMSeg: a multi-view learning model for ultrasound thyroid nodule segmentation
Accurate segmentation of the thyroid gland in ultrasound images is an essential initial step
in distinguishing between benign and malignant nodules, thus facilitating early diagnosis …
in distinguishing between benign and malignant nodules, thus facilitating early diagnosis …
Multi-class classification of thyroid nodules from automatic segmented ultrasound images: Hybrid ResNet based UNet convolutional neural network approach
Background and objectives Early detection and diagnosis of thyroid nodule types are
important because they can be treated more effectively in their early stages. The types of …
important because they can be treated more effectively in their early stages. The types of …
Ultrasound Image Analysis with Vision Transformers
Ultrasound (US) has become a widely used imaging modality in clinical practice,
characterized by its rapidly evolving technology, advantages, and unique challenges, such …
characterized by its rapidly evolving technology, advantages, and unique challenges, such …
Explainable classification of benign-malignant pulmonary nodules with neural networks and information bottleneck
H Zhu, W Liu, Z Gao, H Zhang - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Computerized tomography (CT) is a clinically primary technique to differentiate benign-
malignant pulmonary nodules for lung cancer diagnosis. Early classification of pulmonary …
malignant pulmonary nodules for lung cancer diagnosis. Early classification of pulmonary …
Do as Sonographers Think: Contrast-enhanced Ultrasound for Thyroid Nodules Diagnosis via Microvascular Infiltrative Awareness
Dynamic contrast-enhanced ultrasound (CEUS) imaging can reflect the microvascular
distribution and blood flow perfusion, thereby holding clinical significance in distinguishing …
distribution and blood flow perfusion, thereby holding clinical significance in distinguishing …
Label-Decoupled Medical Image Segmentation with Spatial-Channel Graph Convolution and Dual Attention Enhancement
Deep learning-based methods have been widely used in medical image segmentation
recently. However, existing works are usually difficult to simultaneously capture global long …
recently. However, existing works are usually difficult to simultaneously capture global long …
[HTML][HTML] A narrative review of deep learning in thyroid imaging: current progress and future prospects
WT Yang, BY Ma, Y Chen - Quantitative Imaging in Medicine and …, 2024 - ncbi.nlm.nih.gov
Methods We searched for English-language articles published between April 2018 and
September 2023 in the databases of PubMed, Web of Science, and Google Scholar. The …
September 2023 in the databases of PubMed, Web of Science, and Google Scholar. The …
Pathologist-Like Explanations Unveiled: An Explainable Deep Learning System for White Blood Cell Classification
AS Pal, D Biswas, J Mahapatra… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Despite of achieving remarkable accuracy, the capability of deep learning models for robust
prediction of explanations remains largely unexplored in white blood cells (WBCs) …
prediction of explanations remains largely unexplored in white blood cells (WBCs) …
EBTNet: Efficient Bilateral Token Mixer Network for Fetal Cardiac Ultrasound Image Segmentation
Y Pan, L Niu, X Yang, Q Niu, B Chen - IEEE Access, 2024 - ieeexplore.ieee.org
Fetal cardiac ultrasound apical 4-chamber (A4C) view segmentation with deep learning
technique is a crucial auxiliary to diagnosing congenital heart disease. Due to the …
technique is a crucial auxiliary to diagnosing congenital heart disease. Due to the …