Understanding molecular dynamics at the nanoscale remains challenging due to limitations in the temporal resolution of current imaging techniques. Deep learning integrated with Single-Molecule Localization Microscopy (SMLM) offers opportunities to pr...
Lifetime determination plays a crucial role in fluorescence lifetime imaging microscopy (FLIM). We introduce UNET-FLIM, a deep learning architecture based on a one-dimensional U-net, specifically designed for lifetime determination. UNET-FLIM focuses...
RATIONALE AND OBJECTIVES: This study evaluated StarGAN, a deep learning model designed to generate synthetic computed tomography (sCT) images from magnetic resonance imaging (MRI) and cone-beam computed tomography (CBCT) data using a single model. Th...
BACKGROUND: Tumour vascular density assessed from CD-31 immunohistochemistry (IHC) images has previously been shown to have prognostic value in breast cancer. Current methods to measure vascular density, however, are time-consuming, suffer from high ...
The 5' UTR is critical for mRNA stability and translation efficiency in therapeutics. We developed UTR-Insight, a model integrating a pretrained language model with a CNN-Transformer architecture, explaining 89.1% of the mean ribosome load (MRL) vari...
BACKGROUND: Computed tomography attenuation correction (CTAC) is commonly used in cardiac SPECT imaging to reduce soft-tissue attenuation artifacts. However, CTAC is prone to inaccuracies due to CT artifacts and SPECT-CT mismatch, along with addition...
Thyroid nodules are a common endocrine condition, and accurate differentiation between benign and malignant nodules is essential for making appropriate treatment decisions. Traditional ultrasound-based diagnoses often depend on the expertise of physi...
Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increased number of cases. Pathology diagnoses complemented with predictive and prognostic biomarker information is the first step for personalized treatment....
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural netw...
To develop a deep learning model using transfer learning for automatic detection and segmentation of neck lymph nodes (LNs) in computed tomography (CT) images, the study included 11,013 annotated LNs with a short-axis diameter ≥ 3 mm from 626 head an...
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