Time & Schedule Tuesday, April 27, 2021 Starting from 09:00 till 16:00 No. seats: 30 people
Image Segmentation is a problem in the context of machine vision which is referred as assigning a label to pixel groups (such as abnormalities of medical images) that have common intensity or visual properties. Segmentation of abnormal tissues in medical images is mandatory for locating tumors and pathologies, detecting cancerous regions, and monitoring disease progression. As abnormalities are inherently complex structures, automated segmentation of them is a challenging task. Therefore, more sophisticated techniques are required for accurate modeling and segmentation.
Machine learning as one of the main fields of artificial intelligence uses interdisciplinary techniques to build automated systems. These automated systems are able to process and analyze massive amounts of data to forecast and making decisions without human intervention. Deep Learning (DL) techniques as the latest advances in the field of machine learning are able to perform the task of abnormal tissue segmentation accurately at the clinical level. DL techniques are successful in this task as they generate different levels of abstractions and representations through their deep structures.
- Medical Imaging Processing
- Medical Image Segmentation
- Abnormal Tissue Segmentation
- Challenges of Abnormal Tissue Segmentation
- Convolutional Neural Networks
- CNN Architectures for Segmentation
- Fully Convolutional Networks
- The pipeline of a Typical Deep Method for Segmentation of Abnormal Tissues
- Considered Applications:
- Segmentation of Skin Lesions
- Segmentation of Breast Abnormalities
- Segmentation of Brain Tumors
- Segmentation of Covid-19 Abnormalities in Infected Lungs
- Latest Deep Neural Network Architectural Advances for Segmentation of Abnormal Tissues
About the Workshop
This workshop aims to introduce learners to the main DL segmentation architectures. Moreover, the learners will be able to understand underlying theoretical concepts as well as applying the learned concepts and architectures to different abnormalities in medical images.
Time & Schedule
Tuesday, 27 April 2021
Starting from 09:00 till 16:00
No. seats: 30 people