10Jan

Tissue Analysis with AI

By R. A. / 10/01/2019 / RSIP Vision Learns / No Comments

RSIP Vision is introducing Deep Learning in the biopsy analysis procedure. Here is how the benefits of tissue analysis with AI have become available. Biopsy is the key examination used to determine the presence of most malignant tumors. Notwithstanding its importance and the need for millions of ...

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10Jan

Detection and Tracking of Tumors

By R. A. / 10/01/2019 / RSIP Vision Learns / No Comments

RSIP Vision’s automated detection and tracking of tumors answers one of the most frequent needs in the pharma industry – assessment of patient response to a new drug. This very strong tool saves precious time in the clinical stage when the automated detection and tracking can supply the most accu...

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9Jan

Automated RECIST Measurement

By R. A. / 09/01/2019 / RSIP Vision Learns / No Comments

RSIP Vision has develop an efficient tool for clinical trials in the pharma industry – the automated RECIST measurement. The gold standard in measuring the evolution of solid tumors, along the treatment with a tested drug, is the RECIST score (Response Evaluation Criteria in Solid Tumors), ...

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8Jan

Detection and Segmentation of Dendritic Cells

By R. A. / 08/01/2019 / RSIP Vision Learns / No Comments

Dendritic cells are a type of antigen-presenting cells and have an integral part in the normal functioning immune system, in that they help to initiate primary immune response. Dendritic cells are typically present in tissues that come in contact with the external environment. That includes the s...

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6Jan

Lung Nodules Segmentation

By R. A. / 06/01/2019 / RSIP Vision Learns / No Comments

Pulmonary nodules (AKA lung nodules) are small masses (up to 30mm) of tissue surrounded by pulmonary parenchyma. They are quite common finding on computerized tomography (CT) scans, and although most lung nodules are benign, some are cancerous. Some of the characteristics of the nodules may indic...

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3Jan

Lung Fissures Segmentation

By R. A. / 03/01/2019 / RSIP Vision Learns / No Comments

Lung fissures are double folds of visceral pleura that section the lungs to lobes. Both lungs have an oblique fissure separating the upper and lower lobes, and the right lung has a horizontal fissure separating the right middle lobe from the upper lobe. Identifying these borders is an important p...

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30Dec

Agricultural yield prediction using Deep Learning

By R. A. / 30/12/2018 / RSIP Vision Learns / No Comments

Artificial Intelligence software performing agricultural yield prediction in the field of smart agriculture. Contact our experts to learn how to apply this new technology to your fields. Crop yield prediction in precision agriculture refers to the estimation of seasonal yield before harvesting, b...

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6Dec

Catheter Navigation System with RL

By R. A. / 06/12/2018 / RSIP Vision Learns / No Comments

The typical catheter navigation system relies on fluoroscopy, which exposes patients to dangerous irradiation. To limit the dose throughout the operation, endoscopic cameras are used to guide catheter near the target site of the procedure. When vessel diameter becomes too small to insert an endos...

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15Nov

Intrusion Detection with Deep Learning

By R. A. / 15/11/2018 / RSIP Vision Learns / No Comments

Detecting physical and virtual intrusions is a key process in ensuring information and property security. Physical intrusion detection refers to all attempts at break-ins to a building, warehouse, or other perimeters by an unauthorized person, where access is granted to only limited personnel. Ba...

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14Nov

GAN for non-rigid object tracking

By R. A. / 14/11/2018 / RSIP Vision Learns / No Comments

Object identification and tracking remains a challenging task in computer vision, despite advances in hardware, computational, and algorithmic developments. Difficulties arise, in part, due to the non-rigid nature of objects’ motion, where continuous shape morphing during motion is observed. This...

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16Oct

Chest CT Scan Analysis with Deep Learning

By R. A. / 16/10/2018 / RSIP Vision Learns / No Comments

Chest radiography, with modalities such as X-Ray and CT, is now the common practice for the detection and analysis of the progression of lung tumors, tuberculosis and other pulmonary abnormalities. To date, most analysis are done by expert radiographers, who analyze resulting scans and estimate p...

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15Oct

Object Tracking at High fps

By R. A. / 15/10/2018 / RSIP Vision Learns / No Comments

Object tracking in video sequences is a classical challenge in computer vision, which finds applications in nearly all domains of the industry: from assembly line automation, security, traffic control, automatic driving assistance systems and agriculture. Presently state of the art algorithms per...

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10Oct

High Resolution Image Reconstruction

By R. A. / 10/10/2018 / RSIP Vision Learns / No Comments

Recovering a high-resolution (HR) image from a low resolution one is a classical problem in computer vision for which many algorithms have been developed to date. Most notably, methodologies using sparse coding: these techniques have achieved current state-of-the-art results, but suffer from long...

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3Sep

Temporal point process sampling in video

By R. A. / 03/09/2018 / RSIP Vision Learns / No Comments

Object identification and tracking in a sequence of frames (video) consists of sampling of the scene, by e.g raster or uniform scatter, to extract features and compute their descriptors for target objects identification. This raster scanning procedure can by resource intensive, especially if ever...

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22Aug

RGB-D SLAM building 3D models from depth cameras

By R. A. / 22/08/2018 / RSIP Vision Learns / No Comments

In the past few years, depth cameras became common and easy to get. Several product are available in the market at a reasonable price, e.g. Microsoft Kinect and Intel RealSense. Some recent smartphone also have depth cameras. In this project, we demonstrate our system for creating 3D models from ...

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20Aug

Automated Defect Inspection Using Deep Learning

By R. A. / 20/08/2018 / RSIP Vision Learns / No Comments

Defect detection during production is a necessary step to ensure product quality. Although manual human inspections are still being employed, automated visual inspection has practically replaced manual labor in almost all major production lines and is ubiquitous in mechanical parts manufacturing,...

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14Aug

Deep Learning in Cardiology

By R. A. / 14/08/2018 / RSIP Vision Learns / No Comments

1.1 Segmentation tasks [10] suggest a new fully convolutional network architecture for the task of cardiovascular MRI segmentation. The architecture is based on the idea of network blocks in which each layer is densely connected with auxiliary side paths (skip connections) to all the following la...

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13Aug

Deep Learning in Pulmonology

By R. A. / 13/08/2018 / RSIP Vision Learns / No Comments

Deep learning has been successfully applied in various applications in pulmonary imaging, including CT registration, airway mapping, real time catheter navigation, and pulmonary nodule detection. Some of these applications are still in ongoing development, and here we review few of the most recen...

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12Aug

Deep Learning in Ophthalmology

By R. A. / 12/08/2018 / RSIP Vision Learns / No Comments

Recent works suggest novel deep learning tools for detection, segmentation and characterization of eye disorders. Accurate segmentation of retinal fundus lesions and anomalies in imaging data is an important technical step for early detection and treatment of common eye disorders, and a central a...

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9Aug

Deep Learning in Brain Imaging

By R. A. / 09/08/2018 / RSIP Vision Learns / No Comments

In this article we discuss several recent leading works about Deep Learning in brain imaging and brain microscopy. We organize the works in subsections according to the general algorithmic tasks: segmentation, registration, classification, image enhancement or other tasks. The categories are not ...

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