Buch, Englisch, 592 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1066 g
Medical Imaging and Computer-Aided Diagnosis
Buch, Englisch, 592 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1066 g
Reihe: Lecture Notes in Electrical Engineering
ISBN: 978-981-963862-8
Verlag: Springer Nature Singapore
This book aims to provide a collaborative platform for leading technology minds to exchange insights, foster interdisciplinary dialogue, and propel advancements in both medical imaging and computer-aided diagnosis. As technology evolves, a plethora of state-of-the-art human imaging devices have made remarkable strides in the medical field, transforming diagnostic and treatment standards. Concurrently, there is a growing emphasis on extracting and deciphering extensive information from medical images, spurring the demand for innovative solutions. The fusion of digital image processing and computer vision technologies has paved the way for computer-aided diagnosis (CAD), a pivotal player in disease analysis. This conference extends a warm invitation to researchers, scholars, engineers, scientists, industry leaders, and graduate students active in these fields. Through diverse participation formats, including compelling poster presentations and enlightening oral sessions, attendees will gain profound insights into the intricate interplay between these realms. This book showcases the latest technological breakthroughs, forging valuable connections and envisioning future applications.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
Weitere Infos & Material
.- 1 Oral Cancer Classification using a Hybrid Attention-aided Deep Learning Model.- 2 Deep Learning Frameworks for Histopathological Image Processing in Colorectal Cancer Diagnostics.- 3 Improving Knee Osteoarthritis Detection through a Multitask Learning Method from 2D MRI Slices.- 4 Enhancing Diagnostic Accuracy in Fracture Identification on Musculoskeletal Radiographs Using Deep Learning: A Multi-Reader Retrospective Study, etc.
