Medical Image + Deep Learning Algorithm = Faster Cancer Diagnosis with Better Efficacy
MRI, DICOM 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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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...
Our paper published: Machine learning methods for accurate delineation of tumors in PET images Jakub Czakon, Filip Drapejkowski, Grzegorz Zurek, Piotr Giedziun, Jacek Zebrowski, Witold Dyrka (Submitted on 29 Oct 2016) In oncology, Positron Emission Tomography imaging...
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...
Our team have released our new software package for tumor delineation in PET images. It can be found at github.com/stermedia/SterSEG. Package has been developed in python.