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MEng Projects

The VIA research group typically offers a number of MEng project opportunities. Projects may be done by one or several students. Most projects involve developing algorithms for computer vision and require programming with the VisionX software system. Therefore, there is usually a requirement that students starting in the Fall semester also take ECE5470 at the same time to gain background knowledge in computer vision and familiarity with the VisionX programming tools.

The VIA MEng project program is in two parts with the second conditional on the first. For the first semester the student will plan the project and conduct the background research. At the end of the semester an initial report is required; the continuation of the project to the second semester will be conditional on a satisfactory report submitted at the conclusion of the first semester. If time permits the work on the project research may also be started in the Fall semester. The main activity for the second semester is to conduct the actual research and write up a final report.

The Project Computer Server

The project computer server is All students doing independent projects have accounts on this server for project programming and testing. The environment on rimmer is similar to that for the ECE 5470 platforms: ecelinux-10 and the personal VM. In addition there is a dataset of 50 chest CT images with label maps for different segmented image regions. This data set is the same as the new public image database .

For unix access to the server use the following command from a suitable ssh client:

     ssh -Y ‹NETID›

and log in with your Cornell netid password. There is also web-based access to the image database for convenient browsing and to facilitate image annotation. To access the web server go to: Click on "Request Access", then enter your Cornell NETID credentials.

There is no regular scheduled backup for this server. Make sure that important files have backup copies stored elsewhere.

The Project Topic for Fall 2017

Prof. Reeves will be on sabbatical leave for the Spring semester of 2018; therefore, only be a small number of projects this year. Further, students will need to demonstrate that they are capable of independent work and have made good progress on the project in the Fall semester to be allowed to continue through the Spring semester.

The general project theme is to implement fully automated computer algorithms to identify clinically relevant regions in 3D human CT images of the chest. That is, to design, develop, and evaluate algorithms that will reliably detect unique locations in the human chest.


  1. Segmentation of the scapula
  2. Characterization of image quality by measurements of homogeneous regions of muscle and fat.
  3. Lesion matching in sequential image scans. Locating a pulmonary nodule in a follow up scan.
  4. Implementation of an advanced javascript image viewer with annotations for web browsers. Knowledge of Javascript and Ajax needed for this project.

Required Skills

Self starting person, motivated, interest in computer vision and machine learning; will need to take ECE 5470 “Computer Vision” in the Fall to gain experience in image analysis tools, UNIX and C programming.

Project Course Requirements

  1. Students who are doing a two semester project will be expected to submit an Interim Project Report at the end of the first semester. Note, this report is more detailed that the requirements for the MEng program. In addition it is anticipated that all students will attend a group meeting every two weeks during the semester.
  2. All students doing an MEng project will be required to submit an individual Project Report at the end of the project. Use the class project template for your report. Also review the project draft guidelines


Students interested in doing an MEng project should send an email with their resume and a brief description of their interest to A. P. Reeves