Written By: William Zimmerman Aaron Logan Dylan Reid William Lim Kyungchul Song

1. I.R. S N A pp (ImageReconstructionandSegmentation forNeurosurgeryApplication ) May09-10 Written By: William Zimmerman Aaron Logan Dylan Reid William Lim Kyungchul Song

2. Problem / need statement • Develop an algorithm for Compressed Sensing • Compressed Sensing for MRI • Batch Compress Sensing for Dynamic MRI • Develop an algorithm for Sequential Segmentation (Currently, MRI data is segmented either by hand, or a very slow algorithm.) • To be able to sequentially segment deforming objects or Regions of Interest (ROI's) from the filtered, compressed images. • Utilize prior knowledge about shape change dynamics to segment noisy/low contrast imagery. • Make this process fast enough to run in real-time, using only current and past images for segmentation.

3. Concept sketch / mockup • Example GUI’S • Processing GUI • Segmentation GUI

4. System Description(1/3)

5. System Description(2/3)

6. System Description(3/3)

7. Operating Environment • In summary, these are the attributes of the operating environment: • Linux-based • Fast, multiple-core processing • Lots of memory available • Programs interfaced through command prompt program

8. User Interface Description • The preliminary user interface will consist of running the C++ program in a command prompt window. After the code is closer to a working product, we will create an executable that has a graphical user interface (GUI) that will allow the user to pick different options related to segmentation, and perhaps allow the user to assist the process if necessary. See figure 1 and 2 for general mock-ups

9. Non / Functional Requirement • Functional Requirements • FR001: To translate a matlab algorithm written by Dr. Vaswani’s graduate students, to C++. • FR002: To run experiments with actual MRI data. These experiments will include testing of the  compression algorithm and the sequential segmentation algorithm. • FR003: To check the correctness of our output. This will be tested by comparing output data from the matlab code to the output of our C++ translation. • Non-functional Requirements: • NFR001: The program shall be written in C++. • NFR002: The program shall run faster than in matlab. • NFR003: The program shall be capable of running in real time.

10. Deliverables • The deliverables of our project include • C++ code, well documented and working • An executable of the C++ code • Test data and results from all tests • A complete system that takes raw MR data, first reconstructs the image, and then performs segmentation and outputs the contour • A basic GUI that may allow the user to assist the segmentation process, and also displays segmentation options

11. Market / literature survey • Magnetic resonance imaging (MRI) is an imaging technique used in medical that has a strong market in medical imaging industry. Area such as Radiology uses MRI to visualize structure of body. Images from MRI can be utilized for guiding invasive surgery. This is due to the ability to image soft tissue and organs.

12. Deliverables • The deliverables of our project include: • C++ code, well documented and working • An executable of the C++ code • Test data and results from all tests • A complete system that takes raw MR data, first reconstructs the image, and then performs segmentation and outputs the contour • A basic GUI that may allow the user to assist the segmentation process, and also displays segmentation options

13. R i s k s • Risks with this project mainly relate to the segmentation part. For one, segmentation is very data dependent, and that the data may be too general to output an accurate contour. Also, another risk is that running the KFCS algorithm on a basic PC could cause it to crash, because of the high amount of memory needed to run it.