Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. - Samuel H. Hawkins; John N. Korecki; Yoganand Balagurunathan; Yuhua Gu; Virendra Kumar; Satrajit Basu; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies (IEEE Access, 2014)

A Robust Approach for Automated Lung Segmentation in Thoracic CT. - Hailing Zhou; Dmitry B. Goldgof; Samuel H. Hawkins; Lei Wei 002; Ying Liu; Douglas C. Creighton; Robert J. Gillies; Lawrence O. Hall; Saeid Nahavandi (SMC, 2015)

Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. - Benjamin Geiger; Samuel H. Hawkins; Lawrence O. Hall; Dmitry B. Goldgof; Yoganand Balagurunathan; Robert A. Gatenby; Robert J. Gillies (Computer-Aided Diagnosis, 2016)

Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. - Dmitry Cherezov; Samuel H. Hawkins; Dmitry B. Goldgof; Lawrence O. Hall; Yoganand Balagurunathan; Robert J. Gillies; Matthew B. Schabath (SMC, 2016)

Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. - Rahul Paul; Samuel H. Hawkins; Lawrence O. Hall; Dmitry B. Goldgof; Robert J. Gillies (SMC, 2016)

Lung CT Radiomics: An Overview of Using Images as Data. - Samuel H. Hawkins (2017)

A Comprehensive Review of Deep Learning-Based Methods for COVID-19 Detection Using Chest X-Ray Images. - Saeed S. Alahmari; Baderaldeen Altazi; Jisoo Hwang; Samuel H. Hawkins; Tawfiq Salem (IEEE Access, 2022)