Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Apr 19, 2025
Spectroscopic data often contain artifacts or noise related to the sample characteristics, instrumental variations, or experimental design flaws. Therefore, classifying the raw data is not recommended and might lead to biased results. Nevertheless, m...
OBJECTIVES: Deep learning reconstruction (DLR) has shown promising image denoising ability, but its radiation dose reduction potential remains unknown. The objective of this study was to investigate the diagnostic performance of DLR compared to itera...
International journal of molecular sciences
Apr 18, 2025
Hepatocellular carcinoma (HCC) is a major complication of tyrosinemia type 1 (HT-1), an inborn error of metabolism affecting tyrosine catabolism. The risk of HCC is higher in late diagnoses despite treatment. Alpha-fetoprotein (AFP) is widely used to...
BACKGROUND & AIMS: Atezolizumab plus bevacizumab (A/B) is a first-line therapy for unresectable hepatocellular carcinoma (HCC). Only a small proportion of patients respond to treatment. This study integrated radiomic and clinical data derived from ro...
We had previously reported a convolutional neural network (CNN) based approach, called the holistic kinetic model (HK model 1), for detecting 5-methylcytosine (5mC) by single molecule real-time sequencing (Pacific Biosciences). In this study, we cons...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 13, 2025
Image segmentation is a critical step in computational biomedical image analysis, typically evaluated using metrics like the Dice coefficient during training and validation. However, in clinical settings without manual annotations, assessing segmenta...
The high morbidity and mortality of hepatocellular carcinoma (HCC) impose a substantial economic burden on patients' families and society, and the majority of HCC patients are detected at advanced stages and experience poor therapeutic outcomes, wher...
PURPOSE: To develop machine learning models that are driven by Gd-EOB-DTPA-MRI features for the preoperative prediction of early recurrence in HCC and compare them to the previously proposed ERASL-pre method.
An MRI-only workflow requires synthetic computed tomography (sCT) images to enable dose calculation. This study evaluated the dosimetric and patient positioning accuracy of deep learning-generated sCT for liver radiotherapy.sCT images were generated ...
RATIONALE AND OBJECTIVES: This study aimed to explore the feasibility of using habitat radiomics based on magnetic resonance imaging (MRI) to predict metachronous liver metastasis (MLM) in locally advanced rectal cancer (LARC) patients. A nomogram wa...
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