AI-Enabled Urology – A Clinician’s Perspective
This webinar was held on Wednesday April 19, 2023 Guest speaker: Michael Gorin, M.D. Associate Professor of Urology at Icahn School of Medicine at Mount
Tag: Artificial Intelligence
Machine Learning in Ultrasound Guided Surgery and Intervention
Thursday February 23, 2023 Host: Moshe Safran – CEO of RSIP Vision USA Guest speaker: Dr. Yipeng Hu, Associate Professor at UCL and Affiliated Researcher
Can we trust AI?
Thursday November 17, 2022 Host: Moshe Safran – CEO of RSIP Vision USA Guest speaker: Dr. Paul Yi, Director at the University of Maryland Medical
Challenges and Future of Surgical Robotics
Wednesday September 7, 2022 Host: Moshe Safran – CEO of RSIP Vision USA Guest speaker: Eric Taylor – Senior Director, R&D – Surgical Robotics at
AI-Assisted Brain Surgery
Brain surgeries are very complex: they need to be extremely accurate, since you want to spare healthy tissue; planning is very thorough, as the surgeon
Visualization Modalities for Surgery with AI
Our team has followed with deep attention the recent Hamlyn Symposium. In particular, we have enjoyed the great presentation by Professor Laura Marcu from UC
AI for Structural Heart Procedures
Structural heart diseases include structural deformation of the heart, like valve leakage: the blood flows in two directions and the patient is losing efficiency of
Stone tracking during kidney stone removal
Urolithiasis, or kidney stones, is a common pathology affecting nearly 10% of the population in the USA. There are various treatment options for urolithiasis. The
AI-assisted Surgery for Next Generation Intervention
Wednesday July 27, 2022 Host: Moshe Safran – CEO of RSIP Vision USA Guest speaker: Dr. Sophia Bano – Sr. Research Fellow at University College
Machine Learning in Medical Imaging – Current Challenges
Wednesday June 29, 2022 Host: Moshe Safran – CEO of RSIP Vision USA Guest speaker: Professor Klaus Maier-Hein Klaus Maier-Hein is full professor at Heidelberg
AI-Assisted Tissue Sparing in Urology
Tissue sparing is a common practice during surgeries. This approach aims to remove as little as possible of the surrounding tissue during a procedure. Studies
PCNL – Planning and real-time navigation
Urolithiasis, or kidney stones, is a common pathology affecting nearly 10% of the population in the USA. Percutaneous Nephrolithotomy (PCNL) is a minimally invasive urology
AI and the Future of Radiology
Wednesday January 26, 2022 Host: Moshe Safran – CEO of RSIP Vision USA Guest speaker: Daniel Rueckert, PhD Daniel Rueckert is Professor of Visual Information
Implementing AI to Improve PI-RADS Scoring
Prostate Cancer and PI-RADS scoring Prostate cancer is the most common male cancer in the USA. When diagnosed early, mortality rates are very low, therefore,
Emerging Technologies in AI for Surgical Imaging
Wednesday December 8 at 11am PT Speaker: Moshe Safran (RSIP Vision) Host: Shmulik Shpiro (RSIP Vision) From preoperative planning to intraoperative guidance and post-op analytics,
Announcement – Bladder Panorama Generator and Sparse Reconstruction Tool
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
Announcement – Registration Module for Orthopedic Surgery
RSIP Vision Announces Patient-Specific, Intraoperative Registration Module for Orthopedic Surgery The new neural network technology enables accurate, quantitative measurements of bones and implants during the
Announcement – Automated Assessment of Cartilage Damage
RSIP Vision Announces New Tool for Sports Medicine Applications, Enabling Automated Assessment of Cartilage Damage This new algorithmic software provides automated measurement of articular cartilage
Announcement – Real-Time Surgical Workflow Recognition
RSIP Vision Reveals Its Newest Feat of Medical Imaging Innovation: Real-Time Surgical Workflow Recognition and Analysis Technology for Robotic Assisted Surgeries The company’s newest module
Announcement – MRI to Ultrasound Fusion for Prostate
RSIP Vision Launches an Advanced AI-Based Tool for Prostate MRI and Ultrasound Registration Enabling Precise Navigation in Key Procedures New module creates a warped MRI
Announcement – Robust Metal Implant and Anatomical Segmentation Tool
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
Announcement – Coronary Artery Analysis
RSIP Vision Announces Sophisticated AI-Based Tool for Coronary Artery Analysis and Intervention Planning New module utilizes state-of-the-art deep learning algorithms combined with classic computer vision
Image Analysis and Artificial Intelligence in Urology
Artificial intelligence (AI) and deep learning play an increasingly crucial role in medical imaging in general, and in the field of urology particularly. The applications of AI in urology are numerous, starting with accurate diagnosis (using image segmentation and abnormality detection), continuing with biopsy and operative procedures (using tools for assisted navigation and robotic guidance), and ending in treatment assessment (using tools similar to those used in diagnosis in order to assess the response to treatment).
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One-click segmentation of medical images
In the medical field, image analysis plays a crucial role in both diagnosis and treatment. Its central tool is segmentation, which involves partitioning an image
Image Analysis and AI in Diagnostic ERCP
Recent developments in the field of medical image analysis and artificial intelligence (AI) are used to improve the procedural outcomes of ERCP (Endoscopic retrograde cholangiopancreatography). Here is how RSIP Vision develops AI for diagnostic ERCP. Read what we do for enabling 3D Image Reconstruction and Image Registration/Fusion. Learn how strictures detection and classification can provide the physicians with classification scoring and, sometimes, help them avoid unnecessary biopsies during ERCP.
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Enhanced ERCP tumor assessment using AI
ERCP involves both endoscopy and fluoroscopy on a region with limited access. Accordingly, it poses several challenges for the gastroenterologist performing the procedure: imaging and artificial intelligence are key technologies to solve these challenges. They are used to reconstruct multiangle 2D X-ray images into a 3D image that will help the gastroenterologists in real-time navigation, reducing any complications involved in the navigation process. AI can be trained to accurately classify each tumor found by ERCP and check whether it is cancerous or not.
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AI in ERCP gallstones and strictures treatment
When performing ERCP for stone removal and stricture treatment, the gastroenterologist must overcome several challenges, namely navigation in the region of interest and the choice of the most fitting treatment that must be selected and implemented. AI enables to reconstructing a 3D image from multi-angle X-ray images or ultrasound slices. It is also trained to accurately classify the type of blockage that necessitated the ERCP procedure in the first place, resulting in quicker and more efficient ERCP procedures.
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AI and Robotic Surgery for Renal Cancer
Image analysis techniques and artificial intelligence are leading to radical innovations in renal cancer diagnosis and treatment. In particular, renal cancer robotic surgery. Advanced AI algorithms and computer vision assist in detecting and classifying all kinds of renal diseases, using segmentation and contour detection. This results in improved diagnostic accuracy and enhanced personalized treatment for patients. Moreover, robotic assistance in renal surgeries has gained increased traction in both complete and partial nephrectomies. Surgical planning and 3D reconstruction based on CT and MRI images play vital roles in successful robotic-assisted kidney-related procedures
Announcement – RSIP Vision Announces Versatile Medical Image Segmentation Tool
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
AI and Deep Learning for Prostate Cancer
Recent developments in the field of deep learning and artificial intelligence (AI) are moving the needle in prostate cancer healthcare. More specifically, it is now possible to use state-of-the-art AI and Deep Learning for prostate cancer detection and treatment. Also prostatectomy, a common treatment of prostate cancer, can benefit from the use of these advanced algorithms to increase procedural success. RSIP Vision’s algorithms provide a solution that can be integrated into all steps of prostate cancer care, thus improving patient outcome.
Image Analysis and AI for BPH
Recent developments in the field of deep learning and artificial intelligence can aid in BPH detection, classification and treatment. Analyzing ultrasound and MRI images, and using deep-learning segmentation tools to process them, gives a baseline for severity classification by the physician. Follow-up scans can be accurately compared to baseline scans for optimal treatment decision. Real-time tracking, 3D image reconstruction, and fusion can all provide better guidance during stent placement and urinary tract dilation. Prostatectomy procedure can be kept within boundaries at all times.
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Improving Urolithiasis Healthcare Using AI and Image Analysis
Deep learning and artificial intelligence solutions have recently been developed to improve urolithiasis detection and treatment, leading to enhancing the clinical outcome. Utilizing convolutional neural networks provides accurate stone recognition and segmentation. Automatic Neural-Networks or Support Vector Machine (SVM) classifiers on kidney stone CT data classify the stones into their subtypes with notable accuracy, assisting and speeding treatment selection. Throughout the full cycle of detection and treatment of urolithiasis, RSIP Vision’s custom AI image analysis algorithms significantly improve urolithiasis procedures and outcome.
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Announcement – RSIP Vision Announces New Cardiac Diagnostic Tool for Point-of-Care Ultrasound Screening
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
Announcement – 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,
Announcement – RSIP Vision introduces an innovative set of AI modules for enhanced medical ultrasound applications
RSIP Vision introduces an innovative set of AI modules for enhanced medical ultrasound applications. These innovative modules empower a wide range of medical applications by
PRESS RELEASE – RSIP Vision Supports the CVPR Conference with CVPR Daily Magazine
As the annual event goes virtual, the popular daily publication runs alongside to keep participants informed. SILICON VALLEY, Calif., June 1, 2020 — RSIP Vision,
Announcement – RSIP Vision Launches a Pioneering AI Suite Providing Optimal Solutions to Key Tasks in Lung Surgery
RSIP Vision Launches a Pioneering AI Suite Providing Optimal Solutions to Key Tasks in Lung Surgery. New technology offers critical information enabling pulmonary surgeons to
Announcement – RSIP Vision Announces Breakthrough AI technology for 3D Reconstruction of Knees from X-ray Images
RSIP Vision Announces Breakthrough AI technology for 3D Reconstruction of Knees from X-ray Images. New technology creates a rich 3D modelling of each knee bone
Deep Learning for Cardiac Ultrasound (Echocardiography)
Despite the importance of echocardiography in the diagnosis and treatment of serious cardiac illness, this imaging technology faces two main challenges: Image quality and image assessment. RSIP Vision uses deep learning to enhance both, making it easier for physicians and researchers to interpret findings. As a result, our method resolves user variability, accuracy and efficiency in cardiac ultrasound with advanced, deep learning neural networks. Learn how we do it on our software.
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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
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
Announcement – RSIP Vision Launches a Breakthrough AI-Based Shoulder Replacement Solution
RSIP Vision Launches a Breakthrough AI-Based Shoulder Replacement Solution, Dramatically Improving Clinical Outcome and Shortening Recovery Time. New Technology integrated in medical vendors’ platforms, allows
AI-based Surgical Workflow Analysis, another big step towards the future of robotic surgery
Surgical workflow analysis is an important safety guard for the surgeon: with it, a computer is able to scan a video of a surgery, either offline after it has already been performed or online during the surgery itself, and automatically identify at what stage the surgery is at. Read about RSIP Vision’s approach, built on many years of experience in the development of practical applications.
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Announcement – RSIP Vision Launches AI-Based, 3D Total Hip Replacement Solution
SILICON VALLEY, Calif., Dec 17, 2019 — RSIP Vision, an Israeli global provider of artificial intelligence (AI), computer vision, and image processing technology, announced today a
Announcement – RSIP Vision Introduces AI-Based Multiplex IF Image Analysis Solution
SILICON VALLEY, Calif., Dec 3, 2019 — RSIP Vision, a global leader in artificial intelligence (AI), computer vision, and image processing technology, announced today that
In a heartbeat: Implementing AI in cardiology
Hosts: Moshe Safran and Miki Haimovich – RSIP Vision We’ll discuss Implementing AI in diagnostics as well as intraoperative cardiology applications. “In cardiology, there is increasing use of noninvasive
Brain Ventricles Segmentation with Deep Learning
Early diagnosis and treatment of ventricular system pathologies is crucial. Brain CT has become a leading diagnostic tool due to its high availability and quick image generation, which is useful in emergency room settings such as stroke or traumatic brain injury (TBI). Backed by cutting edge deep neural network and advanced Artificial Intelligence techniques, CT imaging can perform a very accurate brain ventricles segmentation and supply the physicians with crucial information regarding presence of hemorrhage, ischemia, tumors, hydrocephalus, and other pathologies.
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Tissue Analysis with AI
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.
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