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"This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features, discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors, examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods, includes a glossary, an extensive list of references, and an appendix on PCA."

"ABSTRACTMVCT merupakan modalitas pencitraan yang diintegrasikan dengan pesawat Tomoterapi menggunakan energi 3.5 MV yang memiliki andil cukup besar untuk memberikan tindakan terapi yang optimal pada Tomoterapi. Tujuan dari penelitian ini adalah mengevaluasi kualitas citra, estimasi dosis, serta verifikasi posisi pada pencitraan MVCT. Dalam penelitian ini, evaluasi MVCT dilakukan dengan tiga variasi mode slice thickness yaitu fine, normal, dan coarse. Pengujian kualitas citra dilakukan menggunakan phantom Cathpan 600. Estimasi dosis dan verifikasi posisi dilakukan menggunakan phantom Rando pada tiga area yang ditentukan, yaitu head neck, thorax, dan pelvic. Verifikasi posisi dilakukan dengan memberikan beberapa marker eksternal di beberapa titik pada setiap area dan dihitung dengan bantuan dua perangkat lunak, yaitu software Tomoterapi dan 3D Slicer. Hasil evaluasi kualitas citra yang diperoleh menunjukkan bahwa seluruh variasi mode slice thickness pada MVCT masih berada dalam batas toleransi sesuai dengan AAPM TG 148. Estimasi dosis yang diperoleh menunjukkan bahwa dosis terbesar diperoleh pada mode fine. Secara umum, nilai estimasi dosis yang diperoleh berada pada rentang 1-4 cGy untuk semua area pada setiap titik OAR yang diukur. Pergerakan posisi yang diperoleh untuk seluruh variasi mode slice thickness menunjukkan perbedaan yang tidak signifikan, dengan besar le; 0.5 mm. Perbedaan hasil pergerakan posisi yang diperoleh antara dua software yang digunakan tidak lebih dari 0.5 mm.

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ABSTRACTMVCT is an imaging modality which is integrated by Tomotherapy using 3.5 MV energy that has a large enough contribution to provide an optimal therapeutic in Tomotherapy. The purpose of this study is to evaluate the image quality, dose estimation, and verification of the position on MVCT imaging. In this study, MVCT evaluation was performed with three variations of the slice thickness mode that is fine, normal, and coarse. Image quality testing was performed using Catphan 600 phantom. Dose estimation and position verification were performed using Rando phantom in three areas, there were head neck, thorax, and pelvic. Verification of the position was performed by providing several external markers at several points in each area and calculated with the help of two software, namely Tomotherapy software and 3D Slicer. The result of image quality evaluation obtained shows that all variations of slice thickness mode in MVCT are still within tolerable limits in accordance with AAPM TG 148. Estimated dose obtained shows that the largest dose was obtained in fine mode. In general, the estimated dose value which was obtained is in the range of 1 4 cGy for all areas at each measured OAR point which was measured. Movement of position obtained for all variations of slice thickness mode shows insignificant difference, with value le 0.5 mm. The difference of result obtained between the two software used is no more than 0.5 mm."

"Kanker paru-paru, khususnya Non-Small Cell Lung Cancer (NSCLC), dapat diberikan perawatan radioterapi baik untuk tujuan kuratif maupun paliatif. Selama radioterapi, perubahan anatomi pasien dapat terjadi, sehingga radioterapi adaptif menjadi sangat penting. Penelitian ini bertujuan untuk mengevaluasi akurasi registrasi citra deformable pada pasien NSCLC dengan menggunakan dua metode yang berbeda: Intermediate Deformable Image Registration (IDIR) sebagai metode registrasi klasik dan VoxelMorph sebagai metode berbasis pembelajaran mesin. Data yang digunakan adalah citra CT dan CBCT dari 17 pasien NSCLC di Siloam Hospital TB Simatupang, Jakarta Selatan. Citra diberi empat label menggunakan model YOLOv9 dan dievaluasi menggunakan metrik Dice Similarity Coefficient (DSC) serta Mean Distance to Agreement (MDA). Metode IDIR dengan rata-rata runtime 198,128 detik, menghasilkan nilai rata-rata DSC macro 0,786 dan micro 0,923. Rata-rata MDA segmentasi 0,166mm dan MDA dengan ambang batas sebesar 7,218mm. Sementara itu, metode VoxelMorph dengan rata-rata runtime 0,735 detik, menghasilkan nilai rata-rata DSC macro 0,635 dan micro 0,987. Rata-rata MDA segmentasi 0,588mm dan MDA dengan ambang batas sebesar 9,634mm. Hasilnya, evaluasi citra hasil registrasi deformable menunjukkan keberhasilan proses registrasi yang dilakukan. IDIR menunjukkan akurasi tinggi dengan runtime cenderung lebih lama, sedangkan VoxelMorph unggul dalam efisiensi runtime dengan penurunan hasil evaluasi.

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Lung cancer, especially Non-Small Cell Lung Cancer (NSCLC), can be treated with radiotherapy for both curative and palliative purposes. During radiotherapy, anatomical changes in patients may occur, making adaptive radiotherapy crucial. This study aims to evaluate the accuracy of deformable image registration in NSCLC patients using two different methods: Intermediate Deformable Image Registration (IDIR) as a classical registration method and VoxelMorph as a machine learning-based method. The data used consists of CT and CBCT images from 17 NSCLC patients at Siloam Hospital TB Simatupang, South Jakarta. The images were annotated with four labels using the YOLOv9 model and evaluated using Dice Similarity Coefficient (DSC) and Mean Distance to Agreement (MDA) metrics. IDIR method, with an average runtime of 198.128 seconds, yielded average DSC macro values of 0.786 and micro values of 0.923. The average segmentation MDA was 0.166mm, and the boundary MDA was 7.218mm. On the other hand, VoxelMorph method, with an average runtime of 0.735 seconds, produced average DSC macro values of 0.635 and micro values of 0.987. The average segmentation MDA was 0.588mm, and the boundary MDA was 9.634mm. Overall, the evaluation of deformable image registration results indicated successful registration processes. IDIR demonstrated high accuracy with longer runtimes, whereas VoxelMorph excelled in runtime efficiency with slightly lower evaluation results."