PET Image Reconstruction and Deformable Motion Correction Using Unorganized Point Clouds. - Ivan S. Klyuzhin; Vesna Sossi (IEEE Trans. Medical Imaging, 2017)

Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease. - Mohammad R. Salmanpour; Mojtaba Shamsaei; Abdollah Saberi; Saeed Setayeshi 001; Ivan S. Klyuzhin; Vesna Sossi; Arman Rahmim (Comput. Biol. Medicine, 2019)

Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images. - Ivan S. Klyuzhin; Ju-Chieh Cheng; Connor Bevington; Vesna Sossi (IEEE Trans. Medical Imaging, 2020)

Becoming Good at AI for Good. - Meghana Kshirsagar 001; Caleb Robinson; Siyu Yang; Shahrzad Gholami; Ivan S. Klyuzhin; Sumit Mukherjee; Md Nasir; Anthony Ortiz; Felipe Oviedo; Darren Tanner; Anusua Trivedi; Yixi Xu; et al. (AIES, 2021)

3-D PET Image Generation with tumour masks using TGAN. - Robert V. Bergen; Jean-François Rajotte; Fereshteh Yousefirizi; Ivan S. Klyuzhin; Arman Rahmim; Raymond T. Ng (CoRR, 2021)

3D PET image generation with tumour masks using TGAN. - Robert V. Bergen; Jean-François Rajotte; Fereshteh Yousefirizi; Ivan S. Klyuzhin; Arman Rahmim; Raymond T. Ng (Image Processing, 2022)

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features. - Ivan S. Klyuzhin; Yixi Xu; Anthony Ortiz; Juan Lavista Ferres; Ghassan Hamarneh; Arman Rahmim (Comput. Methods Programs Biomed., 2022)

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss. - Yixi Xu; Ivan S. Klyuzhin; Sara Harsini; Anthony Ortiz; Shun Zhang; François Bénard; Rahul Dodhia; Carlos F. Uribe; Arman Rahmim; Juan Lavista Ferres (Comput. Biol. Medicine, 2023)