Lin Meng-Chun, Dung Lan-Rong, Weng Ping-Kuo
Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan.
Biomed Eng Online. 2006 Feb 25;5:14. doi: 10.1186/1475-925X-5-14.
Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam.
We developed an ultra-low-power image compression processor for capsule endoscope or swallowable imaging capsules. In applications of capsule endoscopy, it is imperative to consider battery life/performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much battery power. There are many fast compression algorithms for reducing computation load; however, they may result in distortion of the original image, which is not good for use in the medical care. Thus, this paper will first simplify traditional video compression algorithms and propose a scalable compression architecture.
As the result, the developed video compressor only costs 31 K gates at 2 frames per second, consumes 14.92 mW, and reduces the video size by 75% at least.
胃肠道（GI）内窥镜检查已广泛应用于消化道疾病的诊断，包括克罗恩病、乳糜泻和其他吸收不良症、小肠的良性和恶性肿瘤、血管疾病以及药物相关的小肠损伤。无线胶囊内窥镜已成功用于诊断小肠疾病并减轻患者的不适和疼痛。然而，去马赛克图像的分辨率仍然较低，一些感兴趣的部位可能会被无意遗漏。特别是，当医生放大图像进行详细诊断时，图像会严重失真。提高分辨率可能会导致射频发射器功耗显著增加；因此，为了节省射频发射器的功耗，图像压缩是必要的。为了克服这一缺点，我们一直在开发一种名为GICam的新型胶囊内窥镜。
我们为胶囊内窥镜或可吞咽成像胶囊开发了一种超低功耗图像压缩处理器。在胶囊内窥镜检查的应用中，必须考虑电池寿命/性能的权衡。应用最先进的视频压缩技术可能会因其高压缩率而显著降低图像比特率，但它们都需要密集计算并消耗大量电池电量。有许多快速压缩算法可用于减少计算负荷；然而，它们可能会导致原始图像失真，这不利于医疗应用。因此，本文将首先简化传统视频压缩算法并提出一种可扩展的压缩架构。
结果表明，所开发的视频压缩器在每秒2帧的情况下仅需31K门电路，功耗为14.92mW，且至少可将视频大小减小75%。
