Nihon yakurigaku zasshi. Folia pharmacologica Japonica
Jan 1, 2025
We are living in an era in which AI technology has become widely available and accessible to many people. The field of drug discovery is no exception, and many pharmaceutical companies have actually begun to utilize AI technology in drug discovery re...
INTRODUCTION: This paper examines the impact of transfer learning and CLAHE (Contrast Limited Adaptive Histogram Equalization) optimization on the classification of medical images, specifically brain images.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Fluorescence microscopy is a key method for the visualization of cellular, subcellular, and molecular live-cell dynamics, enabling access to novel insights into mechanisms of health and disease. However, effects like phototoxicity, the fugitive natur...
Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
Jan 1, 2025
BACKGROUND: We retrospectively examined image quality (IQ) of thin-slice virtual monochromatic imaging (VMI) of half-iodine-load, abdominopelvic, contrast-enhanced CT (CECT) by dual-energy CT (DECT) with deep learning image reconstruction (DLIR).
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 1, 2025
Recent studies have revealed that deep neural networks (DNNs) are susceptible to backdoor attacks, in which attackers insert a pre-defined backdoor into a DNN model by poisoning a few training samples. A small subset of neurons in DNN is responsible ...
Advances in experimental medicine and biology
Jan 1, 2025
Retinal degenerative diseases caused by retinal pigment epithelium (RPE) dysfunction affect specific areas of the retina. Regions of molecular and phenotypic RPE heterogeneity have been described in the human eye and are thought to underlie geographi...
This study presents a novel integration of two advanced deep learning models, U-Net and EfficientNetV2, to achieve high-precision segmentation and rapid classification of pathological images. A key innovation is the development of a new heatmap gener...
OBJECTIVE: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
BACKGROUND: The BraTS Generalizability Across Tumors (BraTS-GoAT) initiative addresses the critical need for robust and generalizable models in brain tumor segmentation. Despite advancements in automated segmentation techniques, the variability in tu...
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