Shoulder X-ray images typically have low contrast and high noise levels, making it challenging to distinguish and identify subtle anatomical structures. While existing image enhancement techniques are effective in improving contrast, they often overl...
European journal of nuclear medicine and molecular imaging
Feb 5, 2025
INTRODUCTION: Providing tools for comprehensively evaluating scintigraphy images could enhance transthyretin amyloid cardiomyopathy (ATTR-CM) diagnosis. This study aims to automatically detect and score ATTR-CM in total body scintigraphy images using...
BACKGROUND: Magnetic resonance imaging (MRI) is a highly sensitive modality for diagnosing breast cancer, providing an expanding range of clinical usages that are crucial for the care of women at elevated risk of breast cancer development. Segmentati...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 5, 2025
In recent years, with the increasing attention from researchers towards medical imaging, deep learning-based image segmentation techniques have become mainstream in the field, requiring large amounts of manually annotated data. Annotating datasets fo...
Two-photon fluorescence (TPF) imaging opens a new avenue to achieve high resolution at extended penetration depths. However, it is difficult for conventional TPF imaging systems to simultaneously achieve high resolution and speed. In this work, we de...
Leukocytes are pivotal markers in health, crucial for diagnosing diseases like malaria and viral infections. Peripheral blood smear tests provide pathologists with vital insights into various medical conditions. Manual leukocyte counting is challengi...
Biomedical physics & engineering express
Feb 5, 2025
U-Net is widely used in medical image segmentation due to its simple and flexible architecture design. To address the challenges of scale and complexity in medical tasks, several variants of U-Net have been proposed. In particular, methods based on V...
. We strive to overcome the challenges posed by ring artifacts in x-ray computed tomography (CT) by developing a novel approach for generating training data for deep learning-based methods. Training such networks require large, high quality, datasets...
Medical & biological engineering & computing
Feb 4, 2025
Breast cancer image classification remains a challenging task due to the high-resolution nature of pathological images and their complex feature distributions. Graph neural networks (GNNs) offer promising capabilities to capture local structural info...
Neural networks : the official journal of the International Neural Network Society
Feb 4, 2025
With its ability of joint representation learning and clustering via deep neural networks, the deep clustering have gained significant attention in recent years. Despite the considerable progress, most of the previous deep clustering methods still su...
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