Automatic landmark correspondence detection in medical images with an application to deformable image registration

Purpose: Deformable image registration (DIR) can benefit from additional guidance using corresponding landmarks in the images. However, the benefits thereof are largely understudied, especially due to the lack of automatic landmark detection methods for three-dimensional (3D) medical images. Approach: We present a deep convolutional neural...

Real-time Face and Landmark Localization for Eyeblink-Response Detection: A heterogenous CPU-GPU approach

Pavlovian eyeblink conditioning is a powerful experiment used in the field of neuroscience to measure multiple aspects of how we learn in our daily life. To track the movement of the eyelid during an experiment, researchers traditionally made use of potentiometers or electromyography (EMG). More recently, the use of computer vision and image...

Supervised Learning for Measuring Hip Joint Distance in Digital X-ray Images

Osteoarthritis is a degenerative joint disease which is hard to diagnose objectively and may vary based on the surgeon. This disease is usually diagnosed by measuring several characteristic features of Hip X-rays mainly the joint distance between the femoral head and acetabular cup. Hip joint distance reduction is a clear symptom of...

Database guided detection of anatomical landmark points in 3D images of the heart