Workshop ID: W202203140002
Application of Medical Software Such as SERA, 3D SLICER, MANGO, ITK SNAP in Medicine
Biological & Medical Sciences / Medical / Biomedical Physics

We aim to introduce some popular software such as SERA, 3D SLICER, MANGO, ITK SNAP in medicine. We also aim to go on visualization, delineation (semi and manual segmentation), registration, fusion, and radiomics feature extraction through this software. Moreover, we …

Speaker1: Mohammadreza Salmanpour; Ph.D.
Speaker2: Masod Rezaei; Ph.D.
Speaker3: Ghasem Hjianfar; Master of science
Speaker4: Mahdi Hosseinzadeh; Master of science
Language: Persian
This workshop includes:

0:00 hours

June 2, 2022

Downloadable resources

Vancouver, Canada

Certificate of completion

Timetable:
Title Date Start time End time Duration Video
Application of Medical Software June 2, 2022 21:30 23:59 02:30:00 Video to be uploaded soon
Application of Medical Software June 3, 2022 00:00 02:30 02:30:00 Video to be uploaded soon

Requirements:

Medical physics,Image processing,Medicine



Description:

We aim to introduce some popular software such as SERA, 3D SLICER, MANGO, ITK SNAP in medicine. We also aim to go on visualization, delineation (semi and manual segmentation), registration, fusion, and radiomics feature extraction through this software. Moreover, we apply MRI, PET, CET, and SPECT to this software. Radiomics is a major frontier in medical image analysis, enabling the mining of high-dimensional data from images. Imaging features, beyond pure usage of clinical, have the potential to add further value to the assessment of diseases. Most time, the researchers need to visualize images via some software. Thus, MANGO, ITK SNAP, and 3D SLICER can be employed to visualize the medical images. In addition, to generate new images through fusion techniques, we first need to register images together. We utilize fusion techniques to combine information of different images together. It is proven that fusion techniques enhance the diagnosis and prediction of disease. SERA includes some popular registration, fusion algorithms. Furthermore, SERA includes some image convertors, and it enables you to convert images to each other. Early prediction of the disease may facilitate better temporal therapy, disease control, and identification of disease mechanisms. Thus, beyond the usage of conventional imaging features, the field of radiomics has the potential to provide further analysis of imaging data. SERA has been developed to extract standardized radiomics features. We also aim to introduce SERA to radiomics feature extraction.