Başlık:
Machine Learning in Radiation Oncology Theory and Applications
Yazar:
El Naqa, Issam. editor.
ISBN:
9783319183053
Basım Bilgisi:
1st ed. 2015.
Fiziksel Tanımlama:
XIV, 336 p. 127 illus., 67 illus. in color. online resource.
İçerik:
Introduction: What is Machine Learning -- Computational Learning Theory -- Overview of Supervised Learning Methods -- Overview of Unsupervised Learning Methods -- Performance Evaluation -- Variety of Applications in Radiation Oncology -- Machine Learning for Quality Assurance: Quality Assurance as a Learning Problem -- Detection of Radiotherapy Errors Using Unsupervised Learning -- Prediction of Radiotherapy Errors Using Supervised Learning -- Machine Learning for Computer-Aided Detection: Detection of Cancer Lesions from Imaging -- Classification of Malignant and Benign Tumours -- Machine Learning for Treatment Planning and Delivery -- Image-guided Radiotherapy with Machine Learning: IMRT Optimization Using Machine Learning -- Treatment Assessment Tools -- Machine Learning for Motion Management: Prediction of Respiratory Motion -- Motion-Correction Using Learning Methods -- Machine Learning Application in 4D-CT -- Machine Learning Application in Dynamic Delivery -- Machine Learning for Outcomes Modeling: Bioinformatics of Treatment Response -- Modelling of Norma Tissue Complication Probabilities (NTCP) -- Modelling of Tumour Control Probability (TCP).
Tüzel Kişi Ek Girişi:
Elektronik Erişim:
https://doi.org/10.1007/978-3-319-18305-3Kopya:
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Kütüphane | Materyal Türü | Demirbaş Numarası | Yer Numarası | Durumu/İade Tarihi | Materyal Ayırtma |
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Arıyor... | E-Kitap | 519567-1001 | XX(519567.1) | Arıyor... | Arıyor... |