AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 801 to 810 of 1118 articles

Pulmonary Textures Classification via a Multi-Scale Attention Network.

IEEE journal of biomedical and health informatics
Precise classification of pulmonary textures is crucial to develop a computer aided diagnosis (CAD) system of diffuse lung diseases (DLDs). Although deep learning techniques have been applied to this task, the classification performance is not satisf...

Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network.

IEEE journal of biomedical and health informatics
3D medical image registration is of great clinical importance. However, supervised learning methods require a large amount of accurately annotated corresponding control points (or morphing), which are very difficult to obtain. Unsupervised learning m...

Ultrafast Plane Wave Imaging With Line-Scan-Quality Using an Ultrasound-Transfer Generative Adversarial Network.

IEEE journal of biomedical and health informatics
In the medical ultrasound field, ultrafast imaging has recently become a hot topic. However, the diagnostic reliability of ultrafast high-frame rate plane-wave (PW) imaging is reduced by its low-quality images. The medical ultrasound equipment on the...

Deep Learning-Based Classification of Liver Cancer Histopathology Images Using Only Global Labels.

IEEE journal of biomedical and health informatics
Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of liver cancer and is routinely performed manually. However, this pro...

MediMLP: Using Grad-CAM to Extract Crucial Variables for Lung Cancer Postoperative Complication Prediction.

IEEE journal of biomedical and health informatics
Lung cancer postoperative complication prediction (PCP) is significant for decreasing the perioperative mortality rate after lung cancer surgery. In this paper we concentrate on two PCP tasks: (1) the binary classification for predicting whether a pa...

Heart Sound Segmentation Using Bidirectional LSTMs With Attention.

IEEE journal of biomedical and health informatics
OBJECTIVE: This paper proposes a novel framework for the segmentation of phonocardiogram (PCG) signals into heart states, exploiting the temporal evolution of the PCG as well as considering the salient information that it provides for the detection o...

Leveraging Semantics in WordNet to Facilitate the Computer-Assisted Coding of ICD-11.

IEEE journal of biomedical and health informatics
The International Classification of Diseases (ICD) not only serves as the bedrock for health statistics but also provides a holistic overview of every health aspect of life. This study aims to facilitate the computer-assisted coding of the 11th revis...

Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis.

IEEE journal of biomedical and health informatics
Despite the potential to revolutionise disease diagnosis by performing data-driven classification, clinical interpretability of ConvNet remains challenging. In this paper, a novel clinical interpretable ConvNet architecture is proposed not only for a...

MR-Forest: A Deep Decision Framework for False Positive Reduction in Pulmonary Nodule Detection.

IEEE journal of biomedical and health informatics
With the development of deep learning methods such as convolutional neural network (CNN), the accuracy of automated pulmonary nodule detection has been greatly improved. However, the high computational and storage costs of the large-scale network hav...

CR-Unet: A Composite Network for Ovary and Follicle Segmentation in Ultrasound Images.

IEEE journal of biomedical and health informatics
Transvaginal ultrasound (TVUS) is widely used in infertility treatment. The size and shape of the ovary and follicles must be measured manually for assessing their physiological status by sonographers. However, this process is extremely time-consumin...