Engineering Commons^™

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …

Micro-Ct Of The Human Ossicular Chain: Statistical Shape Modeling And Implications For Otologic Surgery, Western University, London Health Sciences Centre

Electrical and Computer Engineering Publications

The ossicular chain is a middle ear structure consisting of the small incus, malleus and stapes bones, which transmit tympanic membrane vibrations caused by sound to the inner ear. Despite being shown to be highly variable in shape, there are very few morphological studies of the ossicles. The objective of this study was to use a large sample of cadaveric ossicles to create a set of three-dimensional models and study their statistical variance. Thirty-three cadaveric temporal bone samples were scanned using micro-computed tomography (μCT) and segmented. Statistical shape models (SSMs) were then made for each ossicle to demonstrate the divergence …

Intrinsic Measures And Shape Analysis Of The Intratemporal Facial Nerve, Thomas Hudson, Bradley Gare, Daniel Allen, Hanif Ladak, Sumit Agrawal

Electrical and Computer Engineering Publications

Hypothesis: To characterize anatomical measurements and shape variation of the facial nerve within the temporal bone, and to create statistical shape models (SSMs) to enhance knowledge of temporal bone anatomy and aid in automated segmentation.

Background: The facial nerve is a fundamental structure in otologic surgery, and detailed anatomic knowledge with surgical experience are needed to avoid its iatrogenic injury. Trainees can use simulators to practice surgical techniques, however manual segmentation required to develop simulations can be time consuming. Consequently, automated segmentation algorithms have been developed that use atlas registration, SSMs, and deep learning.

Methods: Forty cadaveric temporal bones were …