RSIP Vision Presents New Technology for Intra-op Virtual Measurements in Laparoscopic and Robotic-Assisted Surgeries Innovative Technology Provides Calibration of Robotic-Assisted Surgeries’ (RAS) Images and a
RSIP Vision Presents New Technology for Non-Invasive Planning of Coronary Intervention Innovative technology provides accurate coronary artery 3D reconstruction from 2D angiography to be used
RSIP Vision Introduces Bladder Panorama Generator and Sparse Reconstruction Tool New modules perform stitching of bladder images during cystoscopies, creating a panoramic view and provides
RSIP Vision Unveils Robust Metal Implant and Anatomical Segmentation Tool, for Improved Planning of Specialized Orthopedic Procedures including Revision Arthroplasty Groundbreaking Module Joins RSIP Vision’s Existing
RSIP Vision Announces Versatile Medical Image Segmentation Tool, Delivering Efficient Anatomical Measurements and Better Treatment Options AI-based, domain-agnostic algorithmic module minimizes human errors in clinical
New algorithmic module provides automated expert-level assessment of heart function for point-of-care medical teams enabling a quick and reliable detection of cardiac illness and heart
Upper gastrointestinal cancers, including esophageal cancer and gastric cancer, are among the most common cancers worldwide. However, a lack of endoscopists with colonoscopy skills has been identified and solutions are critically needed. The development of a real-time robust detection system for colorectal neoplasms is needed to significantly reduce the risk of missed lesions during colonoscopy.
New AI technologies by RSIP Vision are very powerful in analysis of tissues and histopathology. This complex task, which has been haunting for years the medical community, has now a very practical solution: deep learning gives very fruitful results to several challenges, like the segmentation of cells and nucleus and the classification of the cells according to the detected pathologies.
RSIP Vision’s oncology software combines detection of lesions and tumors in the human body with tracking those findings along CT scans performed during the research: in particular lung, lymph nodes and liver. These tools enable a quick and accurate assessment of the efficacy of the new treatment.
The golden standard for measuring tumors is the RECIST score. RSIP Vision developed an automated module to accurately measure the RECIST score from CT scans as well as the exact 3D volume of the tumors. Changes in volume are a reliable measure of the progression or remission of the tumor, enabling to evaluate the responsiveness of the treatment in a relatively short time.
Machine vision algorithms are also used to operate robots in the high-precision semiconductor industry. Robots perform these intelligent tasks supported by machine vision software: several methods are currently used to detect defects and classify them, with important economies in both time and money. Robots in the semiconductor industry too can take advantage of deep learning techniques: their main benefit is the dramatic improvement in the defect classification abilities of the robotic devices.
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.
Diabetic Retinopathy (DR) is a leading cause of blindness, especially among adults and even more among the elderly segments of the population. It is associated
Using aerial images taken by drone, plane or satellite, RSIP Vision can create forestry image processing and analysis software to efficiently determine: Trees detection Automatic
Using aerial images taken by drone, plane or satellite, RSIP Vision develops software for image processing and analysis in forestry to efficiently determine: Forest border
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