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People

Principal Investigator

Dafna Sussman

Dafna Sussman

Visit my Teaching page for more information.

Staff

Bita Houshmand (2020-2021)

AI Engineer for the PROTECT study

Christie Tan (2020-2021)

PROTECT Study Coordinator

Master's Students

Adam Lim (2019-2021)

Thesis: Automatic quality assurance algorithm of 3D MRI fetal datasets

Alejo Costanzo (2020-2022)

Thesis: Amniotic fluid segmentation and biometric evaluation

Daniel Nussey (2020-2022)

Thesis: Smart surveillance of secondary brain tumour

Daniel Sare (2019-2021)

Thesis: Development of a placental phantom for MRI sequence optimizations

Daniel Sherman (2020-2022)

Thesis: Rapid classification of endometrial biopsy images using machine learning

Doshina Naila (2019-2021)

Thesis: Synthetic amniotic fluid

Eunyoung Cho (2018-2020)

Thesis: Development of an anthropomorphic fetal phantom for MRI sequence optimization

Justin Lo (2020-2022)

Thesis: Automatic 3D fetal segmentation

Noelle Crasto (2020-2021)

Thesis: Fetal brain phantom

Sid Sadanand (2019-2021)

Thesis: GlucoCEST sequence development and fetal applications

Undergraduate Students

Alex Dunn (2020-2021)

Research: Virtual studio platform development

Danesh Aslam (2020-2021)

Research: Placental segmentation and disease classification

Dylan Young (2020-2021)

Research: COVID-19 in pregnancy data repository

Mitchell Lee (2020-2021)

Research: 3D mechanical design of anthropomorphic MRI fetal phantom

Past Students

Bipin Aasi (2018)

Research: Automatic MR image processing using machine learning

Dylan Young (2019-2020)

Research: Fetal image segmentation and algorithm development

Jillian Cardinell (2019-2020)

Research: Optimization of image augmentation schemes

Jin Cheng (2018-2019)

Research: CEST computer simulation

Justin Lo (2019-2020)

Research: Automatic segmentation algorithm for fetal MRI

Michael Shulman (2018-2019)

Research: Literature review on anthropomorphic MRI phantoms of the human gravid abdomen

Mitchell Lee (2019-2020)

Research: 3D printing and mould-making techniques