Predicting HPV status in oropharyngeal carcinoma using multiparametric MRI and clinical variables

Background: Histopathological examination in the diagnostic workflow of oropharyngeal squamous cell carcinoma (OPSCC) is essential. We aimed to develop a machine learning pipeline to predict human papillomavirus (HPV) status in OPSCC patients based on clinical variables and multiparametric magnetic resonance imaging (MRI). <br/>Methods: In a...

Landslide Detection using Random Forest Classifier

Landslides are destructive and recurrent natural disasters that cost annually significant social and economic losses all over the world. These events can be induced by natural factors as earthquakes and extreme rainfall, as well as by human intervention, including construction and mining. A primary resource to conduct landslides studies for...

Design of an Aberration Correction System for a Deployable Space Telescope

Launch costs for high-resolution space telescopes for Earth observation can be reduced when the telescope mirrors are made deployable. However, such a system is subject to optical aberrations that decreases image quality. To counter these aberrations, an Aberration Correction System (ACS) is proposed that uses a deformable mirror (DM) which is...

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...

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

In this thesis we design, implement and study a high-speed object detection framework. Our baseline detector uses integral channel features as object representation and AdaBoost as supervised learning algorithm. We suggest the implementation of two approximation techniques for speeding up the baseline detector and show their effectiveness by...