Liver Tumor Segmentation with Deep Learning
Liver tumors, also known as hepatic tumors, are quite common and some poses a grim prognosis. Therefore, early detection and diagnosis has become a main goal for lowering mortality and morbidity. Benign tumors include hemangiomas, adenomas, focal nodular hyperplasia (FNH). Although malignant tumo...
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Lymph Node Segmentation Module
Lymph nodes are routinely examined and assessed during physical examination of patients in a clinic or hospital setting. Enlarged lymph nodes can be indicators of infection, cancer and other pathologies. Therefore, a biopsy of a suspected lymph node, which provides tissue histology or cytology is...
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Brain Ventricles Segmentation with Deep Learning
The brain ventricular system is in charge of cerebrospinal fluid (CSF) production, which is essential for its normal function. In addition to providing physical protection to the brain tissue, it provides the nervous system with nutrients and removes waste among other functions. The ventricular s...
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Sinus segmentation with deep learning
The paranasal sinuses are air-filled spaces surrounding the nasal cavity. The sinuses include the maxillary (purple in the image below), frontal (red), ethmoidal (blue) and sphenoidal (green) sinuses. Due to being air filled, the sinuses make the skull lighter and help with filtration of inhaled ...
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Brain Hemorrhage Segmentation with Deep Learning
Intracranial hemorrhage is defined as bleeding within the cranium. Bleeding can occur within the brain parenchyma itself, giving way to what is called intra-axial bleed or intracerebral hemorrhage. On the other hand, bleeding outside the brain tissue is referred to as extra-axial bleed. Subtypes ...
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Dental Segmentation with Deep Learning
Dental problems affect people of all ages and ethnic groups, and are common worldwide. With many patients suffering from tooth decay, orthodontic issues and even oral cancer, the need of oral surgeries and other treatments increases constantly. Recent advancements in technology allow safer and mo...
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Lung vasculature segmentation
Lungs vasculature has a major part in blood oxygenation. The complicated branches of arteries and veins, accompanied by the intricate bronchial tree are in charge of gas exchange, where inhaled air, containing oxygen, enters the lungs and through the bronchial tree it reaches the alveoli. There, ...
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Lung Tumor Segmentation
Lung cancer is the most common cancer related mortality cause among men, and second in women worldwide. Primary lung cancer is usually divided into two groups: Non-Small Cell Lung Cancer (NSCLC), and Small Cell Lung Cancer (SCLC), the former being the most common. In cases that are diagnosed late...
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Tissue Analysis with AI
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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Detection and Tracking of Tumors
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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Automated RECIST Measurement
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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Detection and Segmentation of Dendritic Cells
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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Lung Nodules Segmentation
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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Lung Fissures Segmentation
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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Agricultural yield prediction using Deep Learning
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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Intrusion Detection with Deep Learning
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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Chest CT Scan Analysis with Deep Learning
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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Object Tracking at High fps
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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High Resolution Image Reconstruction
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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