Quantitative Imaging in the Thorax

Ritu Gill, Prabhakar Rajiah (Herausgeber)

Buch | Hardcover

IV, 596 Seiten

2026
Springer International Publishing (Verlag)
978-3-032-14102-6 (ISBN)

Infos

This book offers a comprehensive review of quantitative imaging, from extraction of features to creating AI and machine specific algorithms. Quantitative imaging is the extraction of quantifiable features from images for the assessment of normality, severity, and degree of change. It includes the development, standardization, and optimization of protocols, data analysis, and display/reporting methods to allow for validation of image derived metrics. The radiology report is comprised of both qualitative and quantitative data. The former is narrative, detail oriented, easier for patients and other providers to understand, but difficult to summarize and hard to relate to outcome measures. Quantitative imaging on the other hand is objective and can be used in complex statistical calculations, but cannot really stand alone and needs stringent quality measures in order to preserve accuracy and reproducibility. With an increasing focus on AI and machine learning and the need to build patientand disease specific algorithms, this book offers a common ground for physicians, radiologists and data scientists to reference and further advance the field.

 

The main purpose of this book is to provide details of quantitative imaging from extraction of data from CT and MR images and incorporation into models for clinical translation and application. Individual chapters feature experts from around the world and covers all aspects of quantitative imaging in the thorax, from screening to diagnosis and management. This book also features chapters dedicated to radiomics and radiogenomics.

 

This is an ideal guide for radiologists, physicians, and data scientists working towards a common ground in quantitative imaging.

Autor

Ritu R. Gill, MD, MPH, is Chief of Cardiothoracic Radiology and  Professor of Radiology at Columbia University Medical Center, NY.  She is a subspecialty-trained radiologist with expertise in Cardiothoracic Imaging and Oncoradiology and holds a Master s Degree in Public Health with a concentration in Clinical Effectiveness.

Dr. Gill s scholarly work centers on the integration of quantitative imaging metrics with clinical and pathological parameters to develop prognostic models for thoracic malignancies. Her research seeks to advance the role of imaging as a biomarker in precision oncology, with the goal of improving disease characterization, treatment selection, and survival outcomes in patients with lung and other chest cancers.

In addition to her research and clinical practice, Dr. Gill is actively engaged in academic leadership, education, and editorial work. She has contributed to numerous peer-reviewed publications, book chapters, and educational initiatives in radiology and oncology. As a book editor, Dr. Gill brings a multidisciplinary perspective that bridges imaging science, clinical medicine, and public health, fostering collaborations that drive innovation and evidence-based care in thoracic imaging and oncologic radiology.
 
Prabhakar Rajiah, MBBS, MD, FRCR, FSCMR, FNASCI, is a Professor of Radiology at the Mayo Clinic in Rochester, Minnesota. He completed fellowship training in Cardiovascular Imaging at the University of Washington, Seattle, and the Cleveland Clinic, Cleveland.

Dr. Rajiah s clinical and research interests focus on structural heart disease, multienergy CT, and advanced CT and MRI techniques in cardiovascular imaging. He has published over 170 peer-reviewed manuscripts, authored nine textbooks, edited five books and journals, and contributed 48 book chapters.

He serves as a reviewer for more than 30 scientific journals and is an Associate Editor for several leading publications, including the Journal of Computer Assisted Tomography. Dr. Rajiah is also the current RSNA Eyler Editorial Fellow.

Throughout his distinguished career, Dr. Rajiah has received numerous accolades, including the RSNA Research Trainee Prize (2007), RSNA Roentgen Radiology Fellow Research Award (2008), Teacher of the Year Award (2014), and RSNA Honored Educator Awards (2014, 2020, 2021). He has earned over 50 awards for his scientific presentations at major international conferences such as RSNA and ARRS, and has been an invited speaker at numerous national and international meetings.

Inhalt

Principles of quantitative imaging.- Quantitative techniques in cardiac MRI.- Quantitative CT imaging in coronary artery disease.- CT fractional flow reserve in coronary artery disease.- CT myocardial perfusion imaging.- Quantitative stress perfusion cardiac magnetic resonance.- Quantitative assessment in nuclear cardiology.- Myocardial characterization with CT.- Myocardial characterization with MRI.- Quantitative MRI of valvular heart disease.- Quantitative CT and MRI in transcatheter interventions for structural heart disease.- Quantitative imaging in cardiac electrophysiology.- Quantitative imaging in cardio oncology.- Quantitative imaging of epicardial and pericardial fat.- Quantitative imaging of aorta.- Quantitative imaging of pulmonary hypertension.- Quantitative imaging of pulmonary embolism.- Quantitative imaging in airway diseases.- Quantitative imaging of interstitial lung disease.- Quantitative assessment of lung nodule.- Quantitative assessment of Lung Masses and Lung cancer.- Quantitative imaging in response assessment of lung neoplasms.- Quantitative imaging in pleura.- Quantitative imaging of mediastinal masses.- Quantitative thoracic imaging with nuclear medicine.- Quantitative imaging of sarcopenia.- Applications of artificial intelligence in quantitative imaging.

Produkt-Details

• Erscheint lt. Verlag: 24.2.2026
• Zusatzinfo: IV, 596 p. 272 illus., 202 illus. in color. With online files/update.
• Verlagsort: Cham
• Sprache: englisch
• Maße: 178 x 254 mm
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren
• Schlagworte: Artificial Intelligence • Chest • CT • machine learning • MR • Quantitative Imaging • Thorax
• ISBN-10: 3-032-14102-8 / 3032141028
• ISBN-13: 978-3-032-14102-6 / 9783032141026
• Zustand: Neuware