Medical Segmentation

RSIP Vision is very active in all fields of medical image processing and computer vision applications. Besides all our work in the domains of cardiology, ophthalmology, pulmonology and orthopedics, our engineers have contributed to many other medical segmentation projects helping our clients to improve public health and save thousands of lives. These medical applications in computer vision help physicians perform early identification of major diseases in brain, kidney, prostate and many other organs. Contact us and tell us about your medical computer vision project: we will help you complete with success all medical segmentation tasks.

Deep Learning in Medical Imaging

Until only a few years ago, traditional computer vision techniques have provided excellent results to detection and segmentation task. More recently, with the advent of deep learning  and neural networks also in medical imaging, we obtain surprisingly better results in all task, be it detection, segmentation, classification and the like. In this article we review the state-of-the-art in the newest model in medical image analysis. Read more about Deep Learning in Medical Imaging...

Brain Tumor Segmentation

Tens of thousands of people (including thousands of children) die every year of primary cancerous tumors of the brain and spinal cord. Secondary tumors or brain metastases only make these figures more dramatic. 3D segmentation of brain tumor has high clinical relevance for the estimation of the volume and spread of the tumor. RSIP Vision constructs a probability map to localize the tumor and uses deformable models to obtain the tumor boundaries with zero level energy. Read more...

Prostate Segmentation

Prostate cancer is the second most common cancer among American men, with more than 200,000 new cases diagnosed every year and about 1 man in 7 diagnosed during his lifetime. Volume is a key indicator of the health of the prostate, revealing key information about the stage of the cancer, the probable prognosis and viable treatment. The rich experience of RSIP Vision enables us to recommend an approach based on a semi-automatic prostate segmentation to give a precise estimate of the prostate volume. Read more...

Segmentation of bones and skeleton

A large proportion of the human skeleton is made of porous bone, which offers only low X-ray attenuation, resulting in data density equal to or only slightly higher than that of soft tissues. Bones segmentation and skeleton segmentation using image processing algorithms have become a valuable and indispensable process in many medical applications and have made possible a fast and reliable 3D observation of fractured bones. It's another successful medical application in computer vision by RSIP Vision. Read more...

Automatic segmentation of tumor cells

Visual examination of tumor cells is highly time-consuming and not readily available in clinical applications, where rapid intervention is crucial. Thus, manual segmentation of tumor cells by humans is a quite unpractical and non-trivial task even for experts. Therefore we propose a method for an automatic tumor cells segmentation in histological tissue with variable biomarker expression levels, using computer vision algorithms and machine learning. Read more...

Density Measurement of Cartilage Tissue

Interpretation of ultrasound images of cartilage is challenging since they display no obvious borders in the transition between tissues: the boundary between tissues can morph in both density and texture. Our software can process these problematic ultrasound images and automatically measure the density of cartilage in the knee. The main benefits of this procedure are its non-invasive nature and the efficient and accurate measurement of the cartilage it provides. Read more...

Kidney Segmentation

The most dramatically common kidney diseases are: kidney cancer, hitting 50,000 new patients every year only in the U.S.; and kidney failures, which leave the organ unable to remove wastes. Laparoscopic partial nephrectomy operations remove or reduce kidney tumors and some renal malfunctions. We at RSIP Vision help by providing a semi-automatic and very accurate kidney segmentation technique, built on the study of 4 CT scans and designed to create a kidney model which would be specific for each patient. Read more...
Just before releasing out first version of the product, we encountered new data, and needed to rapidly develop an algorithm for head CT basic segmentation. RSIP Vision were very professional, practical and responsive. They provided a solution quickly and improved it to work on new data we sent them. The communication before and during the project was excellent. The algorithm is still used today in our product, doing a good job on hundreds of CT scans.

~ Yoav Pinsky, Software Engineer / Biosense Webster, a Johnson & Johnson company

We got in touch with RSIP Vision with a challenging project with many adversities and imponderables. The good and successful cooperation with RSIP Vision allowed us to take a big step forward. We really much appreciated their project management and the clear and transparent way of communication! Thank you very much!

~ Christiane Michaelsen, Managing Director / IDENTT SWISS GmbH

"RSIP Vision team was tasked with improving the accuracy and precision of our surgical guidance application. They showed and proved outmost expertise, professionalism and project management skills. They were very tuned to our requirements and requests.
We were very happy with the quality of the work they produced."

~ Latifa McQuiggan and George Polchin / Senior Marketing Manager and Director of Advanced Development

"I would like to thank you again for the amazing work you did with the three MICCAI newsletters. I got positive remarks about it from many attendees."

~ Prof. Leo Joskowicz - Head, Computer-Assisted Surgery and Medical Image Processing Laboratory at The Hebrew University of Jerusalem

"I enjoy working with Ron Soferman and his team at RSIP Vision because it's easy to work with them: they provide clear and timely information and they deliver technology exactly as promised."

~ Dr. Ron Maron / BIRD Foundation