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AI in ImagingThursday - 7/29/2021
Imaging Scientific Session2:00 PM - 3:00 PMTRACK 3

Moderator 1: Maryellen Giger, University of Chicago

Moderator 2: Michael McNitt-Gray, David Geffen School of Medicine at UCLA

2:00 PM
TH-D-TRACK 3-1 : An Effective Deep Learning Framework for Lung Tumor Segmentation in 4D-CT
S. Momin*, Y. Lei, Z. Tian, T. Wang, J. Roper, A. Kesarwala, K. Higgins, J. Bradley, T. Liu, X. Yang
2:07 PM
TH-D-TRACK 3-2 : Automated Tumor Localization and Segmentation Through Hybrid Neural Network in Head & Neck Cancer
A. Qasem*, Z. Zhou
2:14 PM
TH-D-TRACK 3-3 : Deep Siamese Network for False Positive Reduction in Brain Metastases Segmentation
Z. Yang*, M. Chen, R. Timmerman, T. Dan, Z. Wardak, W. Lu, X. Gu
2:21 PM
TH-D-TRACK 3-4 : Development of Artificial Intelligence (AI) Based Platform for Locally Advanced Rectal Cancer Prognosis
Y. Zhang*, L. Shi, X. Sun, S. Jabbour, N. Yue, K. Nie
2:28 PM
TH-D-TRACK 3-5 : Unsupervised COVID-19 Pneumonia Lesion Segmentation in CT Scans Using Cycle Consistent Generative Adversarial Network
Y. Liu*, C. Fang, J. Wen, Y. Yang
2:35 PM
TH-D-TRACK 3-6 : BEST IN PHYSICS (IMAGING): Validation of a Deep-Learning Model Observer in a Realistic Lung-Nodule Detection Task with Convolutional Neural Network-Based CT Denoising
H. Gong*, N. Huber, C. Koo, T. Johnson, A. Inuoe, J. Marsh, J. Thorne, S. Leng, J. Fletcher, C. McCollough, L. Yu
2:42 PM
TH-D-TRACK 3-7 : Towards Understandable AI in Lung Nodule Detection: Using the Genetic Algorithm for Interpretable, Human-Understandable Optimization of Nodule Candidate Generation in Lung CT Imaging
M. Wahi-Anwar*, N. Emaminejad, G. Kim, M. Brown, M. McNitt-Gray