Academic Journal

Conditional random fields for phase‐based lung feature tracking with ultra‐low‐dose x‐rays

التفاصيل البيبلوغرافية
العنوان: Conditional random fields for phase‐based lung feature tracking with ultra‐low‐dose x‐rays
المؤلفون: Jerg, Katharina I., Lyatskaya, Yulia, Stratemeier, Johanna, Hesser, Jürgen W., Aschenbrenner, Katharina P.
المصدر: Medical Physics ; volume 46, issue 5, page 2337-2346 ; ISSN 0094-2405 2473-4209
بيانات النشر: Wiley
سنة النشر: 2019
المجموعة: Wiley Online Library (Open Access Articles via Crossref)
الوصف: Purpose During radiation therapy, a continuous internal tumor monitoring without additional imaging dose is desirable. In this study, a sequential feature‐based position estimation with ultra‐low‐dose (ULD) kV x rays using linear‐chain conditional random fields (CRFs) is performed. Methods Four‐dimensional computed tomography (4D‐CTs) of eight patients serve as a‐priori information from which ULD projections are simulated using a Monte Carlo method. CRFs are trained with Local Energy‐based Shape Histogram features extracted from the ULD images to estimate one out of ten breathing phases from the 4D‐CT associated with the tumor position. Results Compared to a mean accuracy for ±1 breathing phase of 0.867 using a support vector machine (SVM), a mean accuracy of 0.958 results for the CRF with ten incident photons per pixel. This corresponds to a position estimation with a discretization error of 2.4–5.3 mm assuming a linear displacement relation between the breathing phases and a systematic error of 2.0–4.4 mm due to motion underestimation of the 4D‐CT. Conclusions The tumor position estimation is comparable to state‐of‐the‐art methods despite its low imaging dose. Training CRFs further allows a prediction of the following phase and offers a precise post‐treatment evaluation tool when decoding the full image sequence.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1002/mp.13447
الاتاحة: http://dx.doi.org/10.1002/mp.13447
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رقم الانضمام: edsbas.8AA1F0F1
قاعدة البيانات: BASE