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Medical Image + Deep Learning Algorithm = Faster Cancer Diagnosis with Better Efficacy

Digital Pathology

In terms of precision, there are no better methods of seeing a single tissue as… to examine the tissue under the microscope. Every histopathologist would agree that sometimes finding the most descriptive part of the slide is a harder task than it is to make the diagnosis itself. Fortunately, it is not a problem for us. We can localize the most important parts of the slide, what is more, we can extract the very factors that influence diagnostic models the most. We offer Manual Whole Slide Imaging Software (PathoCam) to save pathology images by using your own microscope equipment and PathoViewer to zoom/view, annotate and share it by web/browser.
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MRI, DICOM Analysis

It is one of the most important and most profitable diagnostic tools. Not only this medical imaging modality is not invasive but also can be applied in many different scenarios, obtaining images of pretty much every part of the human body. In case of the prostate cancer, our software/deep learning algorithms can be used to find Region of Interest (ROI), cancer segmentation automatically.

 

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PET Analysis

In oncology, Positron Emission Tomography (PET) imaging is widely used in diagnostics of cancer metastases, in monitoring of progress in course of the cancer treatment, and in planning radiotherapeutic interventions. Accurate and reproducible delineation of the tumor in the PET scans remains a difficult task, despite being crucial for delivering appropriate radiation dose, minimizing adverse side-effects of the therapy, and reliable evaluation of treatment. Our aim is to provide clinicians with intelligent software supporting accurate, efficient and reproducible delineation of the tumor.

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Image Database

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Latest News & Blogs

What is cancer?

Jan 15, 2017 |

Each cell in the human body must follow certain control processes, rules, and regulations as it goes from birth, growth, then to death. Whenever these mechanisms fail to control the cell’s growth, which is due to most cases some genetic damage to the genes—this marks...

We won PETSEG challange!

We won PETSEG challange!

Oct 28, 2016 |

It's good news: Our team won PET segmentation challenge using a data management and processing infrastructure! Automated segmentation of PET images for the delineation of tumor volumes has been the focus of intense research efforts for the last few years. There has...

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