Daniel DiCenzo

Sunnybrook Research Institute

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Articles (14)

Collaborators (3)

Greg Stanisz

Adjunct Professor

Ryerson University

Ali Sadeghi-Naini

Assistant Professor

York University

WILLIAM T TRAN

Assistant Professor

University of Toronto

Daniel DiCenzo

Research Interests

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Articles (14)

Collaborators (3)

Greg Stanisz

Ali Sadeghi-Naini

WILLIAM T TRAN

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Daniel DiCenzo

Research Interests

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Contact this professor

Articles (14)

Quantitative Ultrasound Texture Analysis of Breast Tumors: A Comparison of a Cart-Based and a Wireless Ultrasound Scanner

Predicting Tumor Progression in Patients with Cervical Cancer Using Computer Tomography Radiomic Features

A priori prediction of breast cancer response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivative and molecular subtype

Predicting head and neck cancer treatment outcomes with pre-treatment quantitative ultrasound texture features and optimising machine learning classifiers with texture-of-texture features

MRI texture features from tumor core and margin in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer

A priori prediction of response in multicentre locally advanced breast cancer (LABC) patients using quantitative ultrasound and derivative texture methods

Assessment of clinical radiosensitivity in patients with head-neck squamous cell carcinoma from pre-treatment quantitative ultrasound radiomics

Ultrasound delta-radiomics during radiotherapy to predict recurrence in patients with head and neck squamous cell carcinoma

Quantitative ultrasound radiomics in predicting recurrence for patients with node‐positive head‐neck squamous cell carcinoma treated with radical radiotherapy

Assessment of Clinical Radiosensitivity in Patients with Head-Neck Squamous Cell Carcinoma using Pre-treatment Quantitative Ultrasound Texture-Derivatives and Machine Learning Classifiers

Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer

Breast lesion characterization using Quantitative Ultrasound (QUS) and derivative texture methods

Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies.

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results

Collaborators (3)

Greg Stanisz

Ali Sadeghi-Naini

WILLIAM T TRAN

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