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,
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Success Rating in Robotic Assisted Surgeries
Success Rating and Dynamic Feedback Minimally invasive surgeries (MIS), specifically robotic assisted surgeries (RAS), generally have an improved outcome compared with standard surgeries. However, they
Tissue Sparing in Robotic Assisted Orthopedic Surgeries
Orthopedic surgeries such as hip or knee replacement are performed via an incision which often compromises the surrounding tissue. The assimilation of RAS into these
Procedural Planning in Urology
Challenges in Biopsies There are various types of urological cancers, the most common ones being prostate and kidney cancer. In cancer, early and accurate detection
Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI
Fluoroscopy is an extremely useful imaging tool in surgical procedures in orthopedics, cardiology, GI, etc. In some cases, it is used as a real-time modality
Hyperspectral Imaging for Robotic Assisted Surgery
Standard imaging techniques make use of the visible light spectrum. As is known, the visible light is divided into three bands – red, green, and
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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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,
Tissue Sparing in Robotic Assisted Orthopedic Surgeries
Orthopedic surgeries such as hip or knee replacement are performed via an incision which often compromises the surrounding tissue. The assimilation of RAS into these
Procedural Planning in Urology
Challenges in Biopsies There are various types of urological cancers, the most common ones being prostate and kidney cancer. In cancer, early and accurate detection
Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI
Fluoroscopy is an extremely useful imaging tool in surgical procedures in orthopedics, cardiology, GI, etc. In some cases, it is used as a real-time modality
Hyperspectral Imaging for Robotic Assisted Surgery
Standard imaging techniques make use of the visible light spectrum. As is known, the visible light is divided into three bands – red, green, and
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).
Read More
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.
Read More
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.
Read More
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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