Journal of assisted reproduction and genetics
Apr 3, 2021
In vitro fertilization has been regarded as a forefront solution in treating infertility for over four decades, yet its effectiveness has remained relatively low. This could be attributed to the lack of advancements for the method of observing and se...
Glaucoma is a disease associated with the loss of retinal ganglion cells (RGCs), and remains one of the primary causes of blindness worldwide. Major research efforts are presently directed towards the understanding of disease pathogenesis and the dev...
Journal of bioscience and bioengineering
Oct 17, 2020
Deep learning has emerged as a breakthrough tool for the segmentation of images without supporting human experts. Here, we propose an automated approach that uses deep learning to generate pseudo-nuclear staining of cells from phase contrast images. ...
BACKGROUND: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated...
A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Employing a hybrid artificial intelligence (AI) paradigm that combines traditional rule-based morphological ma...
Translational vision science & technology
Aug 21, 2020
PURPOSE: To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty.
In vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate, in real time, the processes occurring in ...
Laboratory investigation; a journal of technical methods and pathology
Sep 30, 2019
Bone marrow aspirate (BMA) differential cell counts (DCCs) are critical for the classification of hematologic disorders. While manual counts are considered the gold standard, they are labor intensive, time consuming, and subject to bias. A reliable a...
High-content and high-throughput digital microscopes have generated large image sets in biological experiments and clinical practice. Automatic image analysis techniques, such as cell counting, are in high demand. Here, cell counting was treated as a...
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