Tag: Biomedical

Cell Classification - pattern recognition classification techniques

Biomedical image processing and algorithms

Biomedical image processing (or more precisely, biomedical image and signal processing) consists in sophisticated analytical methods and algorithms, ubiquitously found integrated into diagnostic equipment and

Cell Classification software

Whenever the task of classification of single cells is required, RSIP Vision offers pioneering technologies in both segmentation and classification of cells and nuclei. This module includes also the initial task of locating the best area in the slide that might give the best candidate for the classification.

Breakthroughs in biomedical imaging

During the last few decades, the field of biomedical imaging was shaken by major breakthroughs, which have completely changed the way physicians can observe imaging data. For

Microscopy imaging of metastatic cancer cells

Trajectory tracking of a fluorescent tag

Studying the behavior of bio-molecules and the interaction they have with other molecular structures in their native environment, developing indirect measuring procedures based on tracking of single particle, provides valuable information about processes like viral infections of cells, protein-DNA interactions and other complex biological processes. Analysis of trajectories of a tagged particle is one of many RSIP Vision’s projects tracking objects in a sequence of images with dynamic programming, one of our fields of expertise.

Detecting Mitosis Using Deep Neural Networks

State and progression of breast cancer are assessed through prognostic factors, one of which is the mitotic figure. In a histological sample taken from patients, the fraction of breast tissue cells undergoing replication is used to grade the cancer. RSIP Vision’s algorithms allow fast detection, recognition and classification of the mitotic state of a cell using automatic computational autonomous tools: deep neural networks help distinguish complex patterns in images and finally differentiate between mitotic and non-mitotic cells.

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Tag: Biomedical

Biomedical image processing and algorithms

Cell Classification software

Breakthroughs in biomedical imaging

Trajectory tracking of a fluorescent tag

Detecting Mitosis Using Deep Neural Networks

Get in touch

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