3 citations · 6 across the 16 of their papers we have counts for
16 papers
Cancer-Net PCa-MultiSeg: Multimodal Enhancement of Prostate Cancer Lesion Segmentation Using Synthetic Correlated Diffusion Imaging
Jarett Dewbury, Chi-en Amy Tai, Alexander Wong
Current deep learning approaches for prostate cancer lesion segmentation achieve limited performance, with Dice scores of 0.32 or lower in large patient cohorts. To address this li…
Diffusion Decoding for Peptide De Novo Sequencing
Chi-en Amy Tai, Alexander Wong
Peptide de novo sequencing is a method used to reconstruct amino acid sequences from tandem mass spectrometry data without relying on existing protein sequence databases. Tradition…
NL in the Middle: Code Translation with LLMs and Intermediate Representations
Chi-en Amy Tai, Pengyu Nie, Lukasz Golab +1
Studies show that large language models (LLMs) produce buggy code translations. One promising avenue to improve translation accuracy is through intermediate representations, which…
Cancer-Net PCa-Seg: Benchmarking Deep Learning Models for Prostate Cancer Segmentation Using Synthetic Correlated Diffusion Imaging
Jarett Dewbury, Chi-en Amy Tai, Alexander Wong
Prostate cancer (PCa) is the most prevalent cancer among men in the United States, accounting for nearly 300,000 cases, 29\% of all diagnoses and 35,000 total deaths in 2024. Tradi…
Cancer-Net SCa-Synth: An Open Access Synthetically Generated 2D Skin Lesion Dataset for Skin Cancer Classification
Chi-en Amy Tai, Oustan Ding, Alexander Wong
In the United States, skin cancer ranks as the most commonly diagnosed cancer, presenting a significant public health issue due to its high rates of occurrence and the risk of seri…
Enhancing Trust in Clinically Significant Prostate Cancer Prediction with Multiple Magnetic Resonance Imaging Modalities
Benjamin Ng, Chi-en Amy Tai, E. Zhixuan Zeng +1
In the United States, prostate cancer is the second leading cause of deaths in males with a predicted 35,250 deaths in 2024. However, most diagnoses are non-lethal and deemed clini…
Optimizing Synthetic Correlated Diffusion Imaging for Breast Cancer Tumour Delineation
Chi-en Amy Tai, Alexander Wong
Breast cancer is a significant cause of death from cancer in women globally, highlighting the need for improved diagnostic imaging to enhance patient outcomes. Accurate tumour iden…
Enhancing Clinically Significant Prostate Cancer Prediction in T2-weighted Images through Transfer Learning from Breast Cancer
Chi-en Amy Tai, Alexander Wong
In 2020, prostate cancer saw a staggering 1.4 million new cases, resulting in over 375,000 deaths. The accurate identification of clinically significant prostate cancer is crucial…
Improving Breast Cancer Grade Prediction with Multiparametric MRI Created Using Optimized Synthetic Correlated Diffusion Imaging
Chi-en Amy Tai, Alexander Wong
Breast cancer was diagnosed for over 7.8 million women between 2015 to 2020. Grading plays a vital role in breast cancer treatment planning. However, the current tumor grading meth…
Using Multiparametric MRI with Optimized Synthetic Correlated Diffusion Imaging to Enhance Breast Cancer Pathologic Complete Response Prediction
Chi-en Amy Tai, Alexander Wong
In 2020, 685,000 deaths across the world were attributed to breast cancer, underscoring the critical need for innovative and effective breast cancer treatment. Neoadjuvant chemothe…
FoodFusion: A Latent Diffusion Model for Realistic Food Image Generation
Olivia Markham, Yuhao Chen, Chi-en Amy Tai +1
Current state-of-the-art image generation models such as Latent Diffusion Models (LDMs) have demonstrated the capacity to produce visually striking food-related images. However, th…
Cancer-Net PCa-Gen: Synthesis of Realistic Prostate Diffusion Weighted Imaging Data via Anatomic-Conditional Controlled Latent Diffusion
Aditya Sridhar, Chi-en Amy Tai, Hayden Gunraj +2
In Canada, prostate cancer is the most common form of cancer in men and accounted for 20% of new cancer cases for this demographic in 2022. Due to recent successes in leveraging ma…
COVIDx CXR-4: An Expanded Multi-Institutional Open-Source Benchmark Dataset for Chest X-ray Image-Based Computer-Aided COVID-19 Diagnostics
Yifan Wu, Hayden Gunraj, Chi-en Amy Tai +1
The global ramifications of the COVID-19 pandemic remain significant, exerting persistent pressure on nations even three years after its initial outbreak. Deep learning models have…
Cancer-Net PCa-Data: An Open-Source Benchmark Dataset for Prostate Cancer Clinical Decision Support using Synthetic Correlated Diffusion Imaging Data
Hayden Gunraj, Chi-en Amy Tai, Alexander Wong
The recent introduction of synthetic correlated diffusion (CDI) imaging has demonstrated significant potential in the realm of clinical decision support for prostate cancer (PC…
Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images
Chi-en Amy Tai, Elizabeth Janes, Chris Czarnecki +1
Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin ca…
NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches
Chi-en Amy Tai, Matthew Keller, Saeejith Nair +8
Accurate dietary intake estimation is critical for informing policies and programs to support healthy eating, as malnutrition has been directly linked to decreased quality of life.…