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Microscopy

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Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

Journal of microscopy
We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for ex...

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...

Automatic cell counting from stimulated Raman imaging using deep learning.

PloS one
In this paper, we propose an automatic cell counting framework for stimulated Raman scattering (SRS) images, which can assist tumor tissue characteristic analysis, cancer diagnosis, and surgery planning processes. SRS microscopy has promoted tumor di...

A Machine Learning Tool Using Digital Microscopy (Morphogo) for the Identification of Abnormal Lymphocytes in the Bone Marrow.

Acta cytologica
Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological disease. The conventional analysis of bone marrow smears is performed under a manual microscope, which is labor-intensive and subject to interobserver va...

Quick Annotator: an open-source digital pathology based rapid image annotation tool.

The journal of pathology. Clinical research
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest...

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

Virchows Archiv : an international journal of pathology
The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserve...

Time-frequency time-space long short-term memory networks for image classification of histopathological tissue.

Scientific reports
Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultim...

Optical mesoscopy, machine learning, and computational microscopy enable high information content diagnostic imaging of blood films.

The Journal of pathology
Automated image-based assessment of blood films has tremendous potential to support clinical haematology within overstretched healthcare systems. To achieve this, efficient and reliable digital capture of the rich diagnostic information contained wit...

Automated Detection and Diameter Estimation for Mouse Mesenteric Artery Using Semantic Segmentation.

Journal of vascular research
BACKGROUND: Pressurized myography is useful for the assessment of small artery structures and function. However, this procedure requires technical expertise for sample preparation and effort to choose an appropriate sized artery. In this study, we de...