Physics in Medicine and Biology · 2020 · 32 citations · 26 references
MedicineBiomedical EngineeringRadiation OncologyBiomedical ImagingDiagnostic ImagingTreatment PlanningImage-guided RadiotherapyImage-guided TherapyMedical ImagingRadiation Imaging SystemsRadiation TherapyRadiographic ImagingConvolutional Neural Network DetectionConvolutional Neural NetworksDeep Learning In RadiologyImage-guided Cancer TherapyProjectionsSingle-view ProjectionTumor LocalizationTumor Motion Analysis
For tumor tracking therapy, precise knowledge of tumor position in real-time is very important. A technique using single x-ray projection based on a convolutional neural network (CNN) was recently developed which can achieve accurate tumor localization in real-time. However, this method was only validated at fixed gantry angles. In this study, an improved technique is developed to handle arbitrary gantry angles for rotational radiotherapy. To evaluate the highly complex relationship between x-ray projections at arbitrary angles and tumor motion, a special CNN was proposed. In this network, a binary region of interest (ROI) mask was applied on every extracted feature map. This avoids the overfitting problem due to gantry rotation by directing the network to neglect those irrelevant pixels whose intensity variation had nothing to do with breathing motion. In addition, an angle-dependent fully connection layer (ADFCL) was utilized to recover the mapping from extracted feature maps to tumor motion, which would vary with the gantry angles. The method was tested with images from 15 realistic patients and compared with a variant network of VGG, developed by Oxford University's Visual Geometry Group. The tumors were clearly visible on x-ray projections for five patients only. The average tumor localization error was under 1.8 mm and 1.0 mm in superior-inferior and lateral directions. For the other ten patients whose tumors were not clearly visible in the x-ray projection, a feature point localization error was computed to evaluate the proposed method, the mean value of which was no more than 1.5 mm and 1.0 mm in both directions for all patients. A tumor localization method for single x-ray projection at arbitrary angles based on a novel CNN was developed and validated in this study for real-time operation. This greatly expanded the applicability of the tumor localization framework to the rotation therapy.
26
Martin A. Fischler, Robert C. Bolles · Communications of the ACM · 1981 · 25.5K citations · Full text
Prediction of respiratory tumour motion for real-time image-guided radiotherapy
G Sharp, Steve Jiang, Shinichi Shimizu et al. · Physics in Medicine and Biology · 2004 · 354 citations
Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach
Tom Vercauteren, Xavier Pennec, Aymeric Perchant et al. · Lecture notes in computer science · 2008 · 336 citations · Full text
Tokihiro Yamamoto, U. W. Langner, Billy W. Loo et al. · International Journal of Radiation Oncology*Biology*Physics · 2008 · 273 citations · Full text