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Lakshmanan Sannachi

University of Toronto
Sunnybrook Health Sciences Centre

43

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413

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Quantitative ultrasound characterization of therapy response in prostate cancer in vivo.

2021 American Journal of Translational Research
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MRI texture features from tumor core and margin in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer.

2021 Oncotarget
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Early changes in quantitative ultrasound imaging parameters during neoadjuvant chemotherapy to predict recurrence in patients with locally advanced breast cancer

2021
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Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning.

2021 Translational Oncology
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A priori prediction of response in multicentre locally advanced breast cancer (LABC) patients using quantitative ultrasound and derivative texture methods

2021 Oncotarget
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A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning

2020 Scientific Reports
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Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer

2020 Oncotarget
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Assessment of Clinical Radiosensitivity in Patients with Head-Neck Squamous Cell Carcinoma using Pre-treatment Quantitative Ultrasound Texture-Derivatives and Machine Learning Classifiers

2020 International Journal of Radiation Oncology Biology Physics
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Quantitative ultrasound radiomics in predicting recurrence for patients with node‐positive head‐neck squamous cell carcinoma treated with radical radiotherapy

2020 Cancer Medicine
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Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results

2020 PLOS ONE
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