Learning tree-structured representation for 3D coronary artery segmentation
Extensive research has been devoted to the segmentation of the coronary artery. However,
owing to its complex anatomical structure, it is extremely challenging to automatically …
owing to its complex anatomical structure, it is extremely challenging to automatically …
Robust medical image classification from noisy labeled data with global and local representation guided co-training
Deep neural networks have achieved remarkable success in a wide variety of natural image
and medical image computing tasks. However, these achievements indispensably rely on …
and medical image computing tasks. However, these achievements indispensably rely on …
Delta radiomics improves pulmonary nodule malignancy prediction in lung cancer screening
Low-dose computed tomography (LDCT) plays a critical role in the early detection of lung
cancer. Despite the life-saving benefit of early detection by LDCT, there are many limitations …
cancer. Despite the life-saving benefit of early detection by LDCT, there are many limitations …
Cardiac phase detection in echocardiograms with densely gated recurrent neural networks and global extrema loss
Accurate detection of end-systolic (ES) and end-diastolic (ED) frames in an
echocardiographic cine series can be difficult but necessary pre-processing step for the …
echocardiographic cine series can be difficult but necessary pre-processing step for the …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
[HTML][HTML] The higher serum endocan levels may be a risk factor for the onset of cardiovascular disease: a meta-analysis
T Zhao, Y Kecheng, X Zhao, X Hu, J Zhu, Y Wang, J Ni - Medicine, 2018 - journals.lww.com
Objective: Endothelial dysfunction was widely regarded as the initial lesion in the
multifactorial pathogenesis of cardiovascular disease (CVD). Serum endocan, a novel …
multifactorial pathogenesis of cardiovascular disease (CVD). Serum endocan, a novel …
[HTML][HTML] A self-supervised contrastive learning approach for whole slide image representation in digital pathology
Image analysis in digital pathology has proven to be one of the most challenging fields in
medical imaging for AI-driven classification and search tasks. Due to their gigapixel …
medical imaging for AI-driven classification and search tasks. Due to their gigapixel …
Invasive cancer detection utilizing compressed convolutional neural network and transfer learning
Identification of invasive cancer in Whole Slide Images (WSIs) is crucial for tumor staging as
well as treatment planning. However, the precise manual delineation of tumor regions is …
well as treatment planning. However, the precise manual delineation of tumor regions is …
Improving whole slide segmentation through visual context-a systematic study
K Sirinukunwattana, NK Alham, C Verrill… - … Image Computing and …, 2018 - Springer
While challenging, the dense segmentation of histology images is a necessary first step to
assess changes in tissue architecture and cellular morphology. Although specific …
assess changes in tissue architecture and cellular morphology. Although specific …
Pathtr: Context-aware memory transformer for tumor localization in gigapixel pathology images
With the development of deep learning and computation pathology, whole-slide images
(WSIs) are wildly used in clinical diagnosis. The WSI, which refers to the scanning of …
(WSIs) are wildly used in clinical diagnosis. The WSI, which refers to the scanning of …