Wir verwenden Cookies und Analyse-Tools, um die Nutzerfreundlichkeit der Internet-Seite zu verbessern und für Marketingzwecke. Wenn Sie fortfahren, diese Seite zu verwenden, nehmen wir an, dass Sie damit einverstanden sind. Zur Datenschutzerklärung.
Classification of Malignant and Benign Tumours in Digital Mammograms
Details
Breast cancer is one of the most common kinds of cancer, as well as the leading cause of mortality among women. Mammography is currently the most effective imaging modality for the detection of breast cancer and the diagnosis of the anomalies which can identify cancerous cells. Retrospective studies show that, in current breast cancer screenings approximately 15 to 30 percent of breast cancer cases are missed by radiologists. With the advances in digital image processing techniques, it is envisaged that radiologists will have opportunities to decrease this margin of error and hence, improve their diagnosis.
Autorentext
My research in areas including pattern recognition, image processing, computer vision, load forecasting, load profiling, fraud detection, fuzzy logic, neural networks and support vector machines.
Weitere Informationen
- Allgemeine Informationen
- Sprache Englisch
- Herausgeber LAP LAMBERT Academic Publishing
- Gewicht 554g
- Untertitel The Application of Computer Vision and Machine Learning Techniques
- Autor Jawad Nagi
- Titel Classification of Malignant and Benign Tumours in Digital Mammograms
- Veröffentlichung 05.02.2021
- ISBN 613995116X
- Format Kartonierter Einband
- EAN 9786139951161
- Jahr 2021
- Größe H220mm x B150mm x T23mm
- Anzahl Seiten 360
- GTIN 09786139951161