PRESS RELEASE – RSIP Vision Launches a New Knee Segmentation and Landmark Detection from X-ray Module
Breakthrough AI technology leads to precise surgery and optimal implant positioning, resulting in improved quality of life for the patients. SILICON VALLEY, CA, September 15, 2020 – RSIP Vision, a global supplier of medical artificial intelligence (AI), computer vision and image processing ...
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AI for Gastric Cancer Detection
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 ...
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Real time SLAM in Endoscopy Applications
Robotic surgery requires extreme precision due to its small scale and the vulnerable organs such procedures usually target. To be able to get this precision many devices use magnetic or radio based external sensors in order to calculate the endoscope location in the patient’s body. However,...
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Deep Learning for Cardiac Ultrasound (Echocardiography)
Cardiovascular disease at a glance Cardiovascular disease is a leading cause of death, disability and health care expenditure in the United States. Cardiovascular disease (CVD) accounted for 840,678 – or 1 out of 3 – deaths in the US in 2016 Nearly 30 million American adults are curre...
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AI in Cardiac MRI Segmentation
Cardiac magnetic resonance (CMR) imaging plays a critical role in the assessment and management of patients with coronary artery disease (CAD), a leading cause of death worldwide. However, postprocessing is time-consuming and prone to inter and intraobserver variability. Deep learning neural netw...
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AI in cardiac CT angiography
Coronary computed tomography angiography (CCTA) is an efficient and non-invasive imaging modality with widespread clinical implementation in the identification of coronary artery disease (CAD). With rapid 3D visualization of coronary arteries and heart, including visualization of blood flow in ar...
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Endoscopic Procedures using Intravenous OCT
While ultrasound imaging cannot be replaced, adding Intravenous OCT to endoscopy procedures significantly improves image resolution and increases the ability to detect plaque and segment it. Intravenous Optical Coherence Tomography (IVOCT) is a catheter-based medical procedure which uses a near i...
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Using AI to Analyse Intravenous Ultrasound Images
While the low-resolution Intravenous Ultrasound (IVUS) present its challenges, by adding AI to the we can easily overcome this issue, and improve the analysis of blood vessels interior parts for a better clinical outcome. Background Most endoscopic procedures rely on conventional 2D image sensors...
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Segmentation in Orthopedics with Deep Learning
Segmentation is highly important both for examination and planning of knee replacement, hip replacement, shoulder surgery, lesion detection, osteotomy and many other orthopedic procedures. RSIP Vision’s CTO Ilya Kovler and Senior Algorithm Developer Arie Rond explain how to improve the segm...
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Surgical Instrument Segmentation
Using computer vision to identify tools being employed at different stages of a procedure is not only another step toward robotic surgery, it’s a simple, yet very useful tool to streamline and safeguard the surgical process. Surgical instrument (tool) segmentation and classification is a computer...
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AI-based Surgical Workflow Analysis, another big step towards the future of robotic surgery
AI and computer vision technologies can significantly improve the quality of surgical procedures by providing tools that help analyze and monitor certain parts of the surgical workflow. Surgical Workflow Analysis and Surgical Instrument Detection are two good examples of applications that lay the...
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Challenges and AI Solutions for Endoscopy
As endoscopic and microscopic image processing, and surgical vision are evolving as necessary tools for computer assisted interventions (CAI), researchers have recognized the need for common datasets for consistent evaluation and benchmarking of algorithms against each other. The Endoscope Vision...
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Multiplex IF Analysis
Multiplex IF analysis allows for real-time relational data between cells in tissue. This is an advantage over the gold standard brightfield IHC, which looks at a single marker at a time. When using brightfield IHC for multiple markers, sequential sections of the tissue are needed which does not a...
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Circulating Tumor Cells (CTCs)
Circulating tumor cells (CTCs) are rare cancer cells that originate from a tumor and then travel through the patient’s blood or lymphatic system. CTCs have a high risk of metastasizing elsewhere in the body, which can be very dangerous. It is well-known that finding and analyzing these rare cells...
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Detecting Pulmonary Embolism from CT Scan
Pulmonary embolism is a very dangerous condition, which happens when a clot of blood moves from somewhere (generally the legs) to the heart and then finds its way to the lungs. As blood vessels become finer and finer, at some point the clot gets stuck there and blocks the supply of blood, with al...
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PRESS RELEASE – Lung Segmentation with AI
RSIP Vision’s Advanced AI Technology Provides Segmentation with Unmatched Precision for Interventional Lung Procedures. New Solution Enables Surgeons to Biopsy Exact Location of Suspicious Lesions with Minimal Intervention, Avoiding False Negatives and Potential Damage. Jerusalem, July 23, 2019 –...
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Coronary Arteries Segmentation
Coronary artery disease (CAD) or ischemic heart disease (IHD) has become one of the most common causes of morbidity and mortality worldwide. Patients who suffer from CAD, usually have accumulation of deposits such as lipids and inflammatory cells within the coronary arteries, potentially causing ...
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Great Vessels Segmentation with Deep Learning
The great vessels conduct blood to and from the heart. These vessels include the aorta, superior and inferior vena cava, pulmonary arteries and pulmonary veins. Since the great vessels are an integral part of systemic and pulmonary circulation, vascular pathologies involving said vessels might be...
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Middle and Inner Ear Segmentation with Deep Learning
Ear pathologies are common in all age groups, and are one of the leading causes for visiting a doctor. In most cases, proper diagnosis can be achieved via clinical examination. However, in recurrent or complicated cases imaging of the ear is indicated and can help with treatment choice. Th...
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Larynx Segmentation with Deep Learning
The larynx, also known as the voice box, is a triangular structure in charge of important functions including breathing, voice production and supplying protection to the trachea from aspirations. It consists mostly of cartilages- epiglottic, thyroid, cricoid, arytenoid, corniculate and cuneiform....
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