Department of Radiation Oncology, Cancer Hospital Chinese Academy of Medical Sciences, Beijing, China.
J Appl Clin Med Phys. 2019 Sep;20(9):114-121. doi: 10.1002/acm2.12596. Epub 2019 May 9.
Cone-beam computerized tomography (CBCT) is routinely performed for verification of patient position in radiotherapy. It produced a large amount of data which require a method to compress them for efficient storage. In this study three video compression algorithms were introduced and their performance was evaluated based on real patient data.
At first CBCT images in multiple sets of a patient were transferred from reconstruction workstation or exported from treatment planning system. Then CBCT images were sorted according to imaging time (time-prioritized sequence) or imaging location (location-prioritized sequence). Next, this sequence was processed by a video compression algorithm and resulted in a movie. Three representative video compression algorithms (Motion JPEG 2000, Motion JPEG AVI, and MPEG-4) were employed and their compression performance was evaluated based on the CBCT data of 30 patients.
Among three video compression algorithms, Motion JPEG 2000 has the least compression ratio since it is a lossless compression algorithm. Motion JPEG AVI and MPEG-4 have higher compression ratios than Motion JPEG 2000 but come with certain image losses. For MPEG-4, location-prioritized sequences show higher compression ratio than time-prioritized sequences. Based on the results achieved on the clinical target verification application, the registration accuracy of CBCT after decompression was comparable to that of the original CBCT.
Video compression algorithms could provide a higher compression ratio comparing to static image compression algorithm. Although the loss of CBCT image due to compression its impact on registration accuracy of patient positioning is almost negligible. Video compression method is an effective way to substantially reduce the size of CBCT images for storage.
锥形束计算机断层扫描(CBCT)通常用于验证放射治疗中的患者位置。它产生了大量的数据,需要一种方法来压缩它们以实现高效存储。在这项研究中,引入了三种视频压缩算法,并基于真实患者数据评估了它们的性能。
首先将患者多组 CBCT 图像从重建工作站传输或从治疗计划系统导出。然后根据成像时间(时间优先序列)或成像位置(位置优先序列)对 CBCT 图像进行排序。接下来,通过视频压缩算法处理此序列,生成电影。使用了三种代表性的视频压缩算法(Motion JPEG 2000、Motion JPEG AVI 和 MPEG-4),并根据 30 名患者的 CBCT 数据评估了它们的压缩性能。
在三种视频压缩算法中,Motion JPEG 2000 的压缩比最小,因为它是一种无损压缩算法。Motion JPEG AVI 和 MPEG-4 的压缩比高于 Motion JPEG 2000,但会带来一定的图像损失。对于 MPEG-4,位置优先序列的压缩比高于时间优先序列。基于在临床靶区验证应用中获得的结果,压缩后 CBCT 的配准精度可与原始 CBCT 相媲美。
与静态图像压缩算法相比,视频压缩算法可以提供更高的压缩比。尽管 CBCT 图像因压缩而丢失,但对患者定位的配准精度的影响几乎可以忽略不计。视频压缩方法是一种有效减少 CBCT 图像存储大小的方法。