Evaluation of Calcium scoring model on a Chest CT scans
Principal Investigator
Name
Ilyas Sirazitdinov
Degrees
Master degree
Institution
Philips Innovation Labs RUS
Position Title
Junior Scientist
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-603
Initial CDAS Request Approval
Nov 14, 2019
Title
Evaluation of Calcium scoring model on a Chest CT scans
Summary
Ca-scoring is a well-known problem in the medical imaging domain. Modern approaches addressed the problem using Deep Learning methodology, e.g. N. Lessmann et .al.[Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions., 2017] leveraged 2-stage approach based on the training of neural networks. Following this work, we aim to continue research on a Ca-scoring using NLST data.
Aims
- Developing and evaluation of a Calcium scoring model
- Generalization of deep learning based processing pipelines for lung examinations
Collaborators
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