Kanakatte Aparna, Subramanya Rakshith, Delampady Ashik, Nayak Rajarama, Purushothaman Balamuralidhar, Gubbi Jayavardhana
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:1202-1205. doi: 10.1109/EMBC.2017.8037046.
Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.
最近的技术进步促使医学成像领域采用了基于云的创新解决方案。一旦获取了医学图像,就可以在许多设备上进行查看、修改、标注和共享。这一进步主要归功于云计算在医学领域的引入。组织病理学图像很复杂,通常使用显微镜在不同焦距下采集。单个全切片图像包含许多以金字塔结构存储的多分辨率图像,金字塔底部是最高分辨率图像,顶部是最小的缩略图。最高分辨率图像将用于组织病理学诊断和分析。传输和存储如此巨大的图像是一个巨大的挑战。压缩是一种非常有用且有效的技术,可以减小这些图像的大小。由于病理学图像用于诊断,在压缩过程中不能丢失任何信息(无损压缩)。本文提出了一种新颖的方法,即提取组织区域并对该区域应用无损压缩,对空白区域应用有损压缩。由此得到的压缩率以及对组织区域的无损压缩处于可接受范围内,从而允许在云端进行高效的存储和传输。