AIMC Journal:
IEEE journal of biomedical and health informatics
Showing 711 to 720 of 1118 articles
Antibody Supervised Training of a Deep Learning Based Algorithm for Leukocyte Segmentation in Papillary Thyroid Carcinoma.
IEEE journal of biomedical and health informatics
Feb 5, 2021
The quantity of leukocytes in papillary thyroid carcinoma (PTC) potentially have prognostic and treatment predictive value. Here, we propose a novel method for training a convolutional neural network (CNN) algorithm for segmenting leukocytes in PTCs....
Discriminative Feature Network Based on a Hierarchical Attention Mechanism for Semantic Hippocampus Segmentation.
IEEE journal of biomedical and health informatics
Feb 5, 2021
The morphological analysis of hippocampus is vital to various neurological studies including brain disorders and brain anatomy. To assist doctors in analyzing the shape and volume of the hippocampus, an accurate and automatic hippocampus segmentation...
Multi-Task Pre-Training of Deep Neural Networks for Digital Pathology.
IEEE journal of biomedical and health informatics
Feb 5, 2021
In this work, we investigate multi-task learning as a way of pre-training models for classification tasks in digital pathology. It is motivated by the fact that many small and medium-size datasets have been released by the community over the years wh...
Deep Ensemble Feature Network for Gastric Section Classification.
IEEE journal of biomedical and health informatics
Jan 5, 2021
In this paper, we propose a novel deep ensemble feature (DEF) network to classify gastric sections from endoscopic images. Different from recent deep ensemble learning methods, which need to train deep features and classifiers individually to obtain ...
Learning Spatiotemporal Features for Esophageal Abnormality Detection From Endoscopic Videos.
IEEE journal of biomedical and health informatics
Jan 5, 2021
Esophageal cancer is categorized as a type of disease with a high mortality rate. Early detection of esophageal abnormalities (i.e. precancerous and early cancerous) can improve the survival rate of the patients. Recent deep learning-based methods fo...
Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.
IEEE journal of biomedical and health informatics
Jan 5, 2021
The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and ...
Multi-Scale Self-Guided Attention for Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Jan 5, 2021
Even though convolutional neural networks (CNNs) are driving progress in medical image segmentation, standard models still have some drawbacks. First, the use of multi-scale approaches, i.e., encoder-decoder architectures, leads to a redundant use of...
Open-Source Automatic Segmentation of Ocular Structures and Biomarkers of Microbial Keratitis on Slit-Lamp Photography Images Using Deep Learning.
IEEE journal of biomedical and health informatics
Jan 5, 2021
We propose a fully-automatic deep learning-based algorithm for segmentation of ocular structures and microbial keratitis (MK) biomarkers on slit-lamp photography (SLP) images. The dataset consisted of SLP images from 133 eyes with manual annotations ...
A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Since its outbreak in December 2019, the persistent coronavirus disease (COVID-19) became a global health emergency. It is imperative to develop a prognostic tool to identify high-risk patients and assist in the formulation of treatment plans. We ret...
M Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging.
IEEE journal of biomedical and health informatics
Dec 4, 2020
To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic. Considering the limited training cases and resources (e.g, time an...
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