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Examinations, Thesis defences

Master Thesis Defense: Jordan Crawford

Date & time

Friday, February 14, 2020
2 p.m. – 4 p.m.

Speaker(s)

Jordan Crawford

Cost

This event is free

Where

Engineering, Computer Science and Visual Arts Integrated Complex
1515 St. Catherine W. Room EV 3.309

Wheelchair accessible

Yes

Speaker: Jordan Crawford

Supervisors: Drs. T. Fevens, T. Popa

Examining Committee:
Drs. M. Kersten-Oertel, O. Ormandjieva, A. DeLong (Chair)

Title: 3D Visualization of Hill-Sachs Lesions with Articulation

Date: Friday, February 14, 2020

Time: 14:00

Place: EV 3.309

ABSTRACT

A Hill-Sachs Lesion is a wound to the Humeral Head that can result in shoulder instability and recurrent dislocation. The current standard for diagnosis and treatment is for the patient to undergo a CT or MRI scan of the Glenohumeral joint. The attending physician then visually inspects the image slices to infer the actual damage to the Glenoid and humerus to then recommend a proper surgical procedure to correct it.

The treatment options for a Hill-Sachs Lesion vary in complexity, complication rate, chance of recurrence, and resulting joint mobility for the patient. Surgeons will diverge in their choice of correctional surgeries given the same set of CT/MRI images. This can result in a mismatch between the patient’s actual needs and the chosen surgery. We provide a 3D visualization and joint manipulation pipeline to increase the accuracy of diagnoses made by surgeons for treatment of Hill-Sachs Lesions. We transform 2D Dicom data into 3D space, where it may be posed and manipulated to give the surgeon a better view of the damaged site.

We then introduce several convenience functions that solve for positions that are of interest when assessing the possibility of re-engagement and re-dislocation. We also present the ability to position the 3D data at solved-for positions, and to make use of a calibrated VR orientation tool named Myo Bracelet to position and animate the humerus as if it were the patient’s arm. We believe these steps allow simple and intuitive manipulation of the data that better represents the scenarios that surgeons visualize when planning their surgery.

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