AI Medical Compendium Topic

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Diagnosis, Computer-Assisted

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Attention-based generative adversarial network in medical imaging: A narrative review.

Computers in biology and medicine
As a popular probabilistic generative model, generative adversarial network (GAN) has been successfully used not only in natural image processing, but also in medical image analysis and computer-aided diagnosis. Despite the various advantages, the ap...

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Computational and mathematical methods in medicine
Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate of patients is improved by early detection. With the development of object detection technology based on deep learning, computer-aided diagnosis of c...

End-to-end deep learning framework for printed circuit board manufacturing defect classification.

Scientific reports
We report a complete deep-learning framework using a single-step object detection model in order to quickly and accurately detect and classify the types of manufacturing defects present on Printed Circuit Board (PCBs). We describe the complete model ...

Identification and Classification of Prostate Cancer Identification and Classification Based on Improved Convolution Neural Network.

BioMed research international
Prostate cancer is one of the most common cancers in men worldwide, second only to lung cancer. The most common method used in diagnosing prostate cancer is the microscopic observation of stained biopsies by a pathologist and the Gleason score of the...

Single-shot retinal image enhancement using untrained and pretrained neural networks priors integrated with analytical image priors.

Computers in biology and medicine
Retinal images acquired using fundus cameras are often visually blurred due to imperfect imaging conditions, refractive medium turbidity, and motion blur. In addition, ocular diseases such as the presence of cataracts also result in blurred retinal i...

HPM-Net: Hierarchical progressive multiscale network for liver vessel segmentation in CT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The segmentation and visualization of liver vessels in 3D CT images are essential for computer-aided diagnosis and preoperative planning of liver diseases. Due to the irregular structure of liver vessels and image noise, acc...

Self-Supervised Bi-Channel Transformer Networks for Computer-Aided Diagnosis.

IEEE journal of biomedical and health informatics
Self-supervised learning (SSL) can alleviate the issue of small sample size, which has shown its effectiveness for the computer-aided diagnosis (CAD) models. However, since the conventional SSL methods share the identical backbone in both the pretext...

A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images.

IEEE journal of biomedical and health informatics
The spatial correlation among different tissue components is an essential characteristic for diagnosis of breast cancers based on histopathological images. Graph convolutional network (GCN) can effectively capture this spatial feature representation,...

Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach.

Computational and mathematical methods in medicine
Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to detect brain tumors early. Recent claims have been made that computer-aided diagnosis-based systems can ...

Detection of mitotic HEp-2 cell images: role of feature representation and classification framework under class skew.

Medical & biological engineering & computing
We propose and analyze a framework to detect and identify the mitotic type staining patterns among different non-mitotic (interphase) patterns on HEp-2 cell substrate specimen images. This is considered as a principal task in computer-aided diagnosis...