Inspiration
Our passion is to ignite hope from middle of darkness. Sympathizing with cancer patient's pain. Transforming their painful CT Scans images into a joyful Saudi national dance "AL-Aradha" that represents unity and support. "Al-Aradha" is a folkloric group dance that was historically performed at war and is now performed at weddings and celebrations. The performers dancing holding the hands of each other, supporting each other, to form one body dancing synchronically.
Software
D2P: Converting Medical CT images from .DICOM into .STL 3D models 3D Slicer: Create segmentation of the cancer area in 3D model of the skull BASH: Utilizing Bash to process and orchestrate steps to finalize the output Curl: handle the communication with the Deep AI model to apply the style DeepAI: Applying the the “Style transfer” model ImageMagick: Managing the resolution and additional image transformation FFMPEG: Slicing the video to images and converting them back to a video clip
AI Modules & Datasets
AI Modules: We choose to use Fast Style transfer model since we want to apply multiple CT scans to different imagery of the dance to create a continence dance motion with variety of look and feel. Datasets: CT Scans images of 4 different cancer patients, contain 1200 slice.
From Phase 1 to Phase 2
We have transform the Art from a still image to a video and we have used a additional set of CT scan Images and different orientation of the Scans to produce different styles and outputs
Built With
- 3dslicer
- bash
- d2p
- deepai
- mmfpeg
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