Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Nov 20, 2025
PURPOSE: To assess the effects of industry-developed deep learning reconstruction with super resolution (DLR-SR) on single-shot turbo spin-echo (SshTSE) images with thickness of 2 mm with DLR (SshTSE) relative to those of images with a thickness of 5...
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Nov 20, 2025
PURPOSE: To evaluate the effect of model-based deep-learning reconstruction (DLR) compared with that of compressed sensing-sensitivity encoding (CS) on cine cardiac magnetic resonance (CMR).
This study aimed to explore a discriminant method for cervical squamous epithelial cells based on computer image analysis to establish a foundation for artificial intelligence diagnosis of cervical cancer. A total of 1682 cells were captured from 53 ...
The American journal of tropical medicine and hygiene
Nov 5, 2025
Snakebites pose a significant global health challenge. The timely and accurate identification of snake species is essential for guiding antivenom administration. Our goal was to evaluate the effectiveness of a machine learning model for classifying s...
Segmenting multidimensional microscopy data requires high accuracy across many images (e.g., time points or Z slices) and is thus a labor-intensive part of biological image processing pipelines. We present ReSCU-Nets, recurrent convolutional neural n...
AJNR. American journal of neuroradiology
Nov 3, 2025
BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction has been successful in realizing otherwise impracticable acceleration factors and improving image quality in conventional MRI field strengths; however, there has been limited application to ul...
Fourier ptychography microscopy (FPM) has made significant progress since its invention in 2013, thanks to its adaptable nature, high resolution, and vast field-of-view capabilities. FPM is used in various medical applications across multiple optical...
PURPOSE: Chemical exchange saturation transfer (CEST) imaging is highly sensitive to patient motion, which can compromise the reliability of quantitative molecular analysis. This study aims to develop and validate a deep learning-based motion correct...
OBJECTIVES: Artifacts in clinical MRI can compromise the performance of AI models. This study evaluates how different data augmentation strategies affect an AI model's segmentation performance under variable artifact severity.
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