TPU Cloud-Based Generalized U-Net for Eye Fundus Image Segmentation
Luna Perejón, Francisco
Vicente Díaz, Saturnino
Rodríguez Corral, José María
Civit Balcells, Antón
|Department||Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores|
|Published in||IEEE Access, 7, 142379-142387.|
|Abstract||Medical images from different clinics are acquired with different instruments and settings.
To perform segmentation on these images as a cloud-based service we need to train with multiple datasets
to increase the ...
Medical images from different clinics are acquired with different instruments and settings. To perform segmentation on these images as a cloud-based service we need to train with multiple datasets to increase the segmentation independency from the source. We also require an ef cient and fast segmentation network. In this work these two problems, which are essential for many practical medical imaging applications, are studied. As a segmentation network, U-Net has been selected. U-Net is a class of deep neural networks which have been shown to be effective for medical image segmentation. Many different U-Net implementations have been proposed.With the recent development of tensor processing units (TPU), the execution times of these algorithms can be drastically reduced. This makes them attractive for cloud services. In this paper, we study, using Google's publicly available colab environment, a generalized fully con gurable Keras U-Net implementation which uses Google TPU processors for training and prediction. As our application problem, we use the segmentation of Optic Disc and Cup, which can be applied to glaucoma detection. To obtain networks with a good performance, independently of the image acquisition source, we combine multiple publicly available datasets (RIM-One V3, DRISHTI and DRIONS). As a result of this study, we have developed a set of functions that allow the implementation of generalized U-Nets adapted to TPU execution and are suitable for cloud-based service implementation.
|Cite||Civit-Masot, J., Luna Perejón, F., Vicente Díaz, S., Rodríguez Corral, J.M. y Civit Balcells, A. (2019). TPU Cloud-Based Generalized U-Net for Eye Fundus Image Segmentation. IEEE Access, 7, 142379-142387.|