Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography

Author:

Orooji Mahdi1,Alilou Mehdi1,Rakshit Sagar2,Beig Niha1,Khorrami Mohammad Hadi1,Rajiah Prabhakar3,Thawani Rajat1,Ginsberg Jennifer4,Donatelli Christopher5,Yang Michael6,Jacono Frank5,Gilkeson Robert7,Velcheti Vamsidhar8,Linden Philip4,Madabhushi Anant1

Affiliation:

1. Case Western Reserve University, Department of Biomedical Engineering, Cleveland, Ohio

2. Cleveland Clinic Foundation, Department of Medicine, Cleveland, Ohio

3. UT Southwestern, Department of Radiology, Dallas, Texas

4. University Hospitals Cleveland Medical Center, Division of Thoracic and Esophageal Surgery, Clevelan

5. University Hospitals Cleveland Medical Center, Division of Pulmonary and Critical Care, Department o

6. University Hospitals Cleveland Medical Center, Department of Pathology, Cleveland, Ohio

7. University Hospitals Cleveland Medical Center, Department of Radiology, Cleveland, Ohio

8. Cleveland Clinic Foundation, Department of Solid Tumor Oncology, Cleveland, Ohio

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology, Nuclear Medicine and imaging

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4. Feature selection methods and predictive models in CT lung cancer radiomics;Journal of Applied Clinical Medical Physics;2022-12-17

5. A Survey of Dental Caries Segmentation and Detection Techniques;The Scientific World Journal;2022-04-11

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