A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
Artificial intelligence in ultrasound
YT Shen, L Chen, WW Yue, HX Xu - European Journal of Radiology, 2021 - Elsevier
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Elsevier logo Journals & Books Search RegisterSign in View PDF Download full issue …
Elsevier logo Journals & Books Search RegisterSign in View PDF Download full issue …
A generic deep learning framework to classify thyroid and breast lesions in ultrasound images
Breast and thyroid cancers are the two common cancers to affect women worldwide.
Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast …
Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast …
A novel attention-guided convolutional network for the detection of abnormal cervical cells in cervical cancer screening
Early detection of abnormal cervical cells in cervical cancer screening increases the
chances of timely treatment. But manual detection requires experienced pathologists and is …
chances of timely treatment. But manual detection requires experienced pathologists and is …
[HTML][HTML] Ai in thyroid cancer diagnosis: Techniques, trends, and future directions
Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
Deep convolutional neural networks in thyroid disease detection: a multi-classification comparison by ultrasonography and computed tomography
Abstract Background and Objective: As one of the largest endocrine organs in the human
body, the thyroid gland regulates daily metabolism. Early detection of thyroid disease leads …
body, the thyroid gland regulates daily metabolism. Early detection of thyroid disease leads …
Automated thyroid nodule detection from ultrasound imaging using deep convolutional neural networks
Thyroid cancer is the most common endocrine cancer and its incidence has continuously
increased worldwide. In this paper, we focus on the challenging problem of nodule detection …
increased worldwide. In this paper, we focus on the challenging problem of nodule detection …
A regional-attentive multi-task learning framework for breast ultrasound image segmentation and classification
Breast ultrasound (BUS) imaging is commonly used in the early detection of breast cancer
as a portable, valuable, and widely available diagnosis tool. Automated BUS image …
as a portable, valuable, and widely available diagnosis tool. Automated BUS image …
MDC-net: A new convolutional neural network for nucleus segmentation in histopathology images with distance maps and contour information
Accurate segmentation of nuclei in digital pathology images can assist doctors in diagnosing
diseases and evaluating subsequent treatments. Manual segmentation of nuclei from …
diseases and evaluating subsequent treatments. Manual segmentation of nuclei from …
Convolutional neural network and transfer learning based mineral prospectivity modeling for geochemical exploration of Au mineralization within the Guandian …
H Li, X Li, F Yuan, SM Jowitt, M Zhang, J Zhou… - Applied …, 2020 - Elsevier
Abstract The Zhangbaling–Guandian area is located in the eastern part of Anhui Province,
China, and contains several small Au-Cu deposits and occurrences that highlight the …
China, and contains several small Au-Cu deposits and occurrences that highlight the …