Biomedical Image Segmentation
The project is centered around analysis of human cells particularly cancer cells found in histopathological images for upstream therapeutic benefit. The pipeline is to be incorporated into the patient centric platform at https://tison.lums.edu.pk/
Project Title
Biomedical Image Segmentation
Project Area of Specialization
Project Summary
The project is centered around analysis of human cells particularly cancer cells found in histopathological images for upstream therapeutic benefit. The pipeline is to be incorporated into the patient centric platform at https://tison.lums.edu.pk/
Project Objectives
Major objective is to provide an image analysis pipeline for histopathological images which are routinely conducted in cancer hospitals for cancer patients
Project Implementation Method
Techniques from computer vision and image processing will be applied to perform analysis of histopathological images which will integrated with the system at https://tison.lums.edu.pk/ and allow an interface to process results
Benefits of the Project
The benefits of artificial intelligence have the potential to transform the healthcare system in pakistan which is still under serving its people. Hospital staff can easily perform image analysis through our proposed project by utilizing the web interface at https://tison.lums.edu.pk/
Technical Details of Final Deliverable
A convolutional neural network will be trained on a large number of histopathology images taken from the Cancer Imaging Archive (https://www.cancerimagingarchive.net/) which will allow the network to predict and segment cellular regions in the images and image processing technqiues will be used to provide various metrics like cellular count, density, area amongnst other metrics
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| GPU Card 1 | Equipment | 1 | 70000 | 70000 |
| GPU Card 1 | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 80000 |
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