Resumen de Image compression for medical diagnosis using neural networks

Laura Cristina Lanzarini , María Teresa Vargas Camacho, Amado Flores Badrán, Armando De Giusti

• Images compression is a widely studied topic. Conventional situations offer variable compression ratios depending on the image in question and, in general, do not yield good results for images that are rich in tones. This work is an application of images compression of patient s computed tomographies using neural networks, which allows to carry out both compression and decompression of the images with a fixed ratio of 8:1 and a loss of 2%.