TY - GEN
T1 - Using Machine Learning for Precision Prognostics in Head and Neck Cancer Images
AU - Rao, Divya
AU - Prakashini, null
AU - Singh, Rohit
AU - Vijayananda,
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/5/15
Y1 - 2022/5/15
N2 - Radiomics is a new and emerging field that leverages advancements in machine learning and computational capabilities to provide prognostic and diagnostic outcomes. Using standard medical imaging techniques used to assess the location and spread of the tumor, radiomics is used to compute a wealth of information using sub-visual features from existing images to identify cancer biomarkers. This paper explores the various applications of radiomics, specifically in head and neck cancer imaging. We provide a detailed radiomics workflow for medical image data. We identify the various applications and highlight relevant research works in these applications. We address the challenges faced in the field and highlight future work in this area. This work is helpful to those researchers interested in interdisciplinary research focused on image processing in the Head and Neck anatomy.
AB - Radiomics is a new and emerging field that leverages advancements in machine learning and computational capabilities to provide prognostic and diagnostic outcomes. Using standard medical imaging techniques used to assess the location and spread of the tumor, radiomics is used to compute a wealth of information using sub-visual features from existing images to identify cancer biomarkers. This paper explores the various applications of radiomics, specifically in head and neck cancer imaging. We provide a detailed radiomics workflow for medical image data. We identify the various applications and highlight relevant research works in these applications. We address the challenges faced in the field and highlight future work in this area. This work is helpful to those researchers interested in interdisciplinary research focused on image processing in the Head and Neck anatomy.
UR - http://www.scopus.com/inward/record.url?scp=85140012261&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85140012261&partnerID=8YFLogxK
U2 - 10.1145/3545729.3545734
DO - 10.1145/3545729.3545734
M3 - Conference contribution
AN - SCOPUS:85140012261
T3 - ACM International Conference Proceeding Series
SP - 14
EP - 17
BT - ICMHI 2022 - 2022 6th International Conference on Medical and Health Informatics
PB - Association for Computing Machinery, Inc
T2 - 6th International Conference on Medical and Health Informatics, ICMHI 2022
Y2 - 12 May 2022 through 15 May 2022
ER -
