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Wienert S, Heim D, Kotani M, Lindequist B, Stenzinger A, Ishii M, Hufnagl P, Beil M, Dietel M, Denkert C, Klauschen F. CognitionMaster: an object-based image analysis framework. Diagn Pathol 2013, 8:34
...The performance of a typical bicubic upscale operation is typically in the order of 10 times faster than via the standard AWT mechanism using RenderingHints.VALUE_INTERPOLATION_BICUBIC.
The library depends on Aparapi (https://code.google.com/p/aparapi/). Any GPU supporting OpenCL should be supported (including low-end GPUs without double-precision fp support), and there is automatic fallback to pure java implementations for all operations in the event that there is no OpenCL support available.
A high-level API allows for very easy use from AWT/Swing, whilst the low-level array-based API allows integration with any imaging framework (e.g. from Android or SWT).
...Finding patient disease started by taking Fourier transform (FFT) from input signal and extract a single cycle. Based on some heuristic algorithm the most important feature like P , Q , R , S , T captured and feed to trained neural network. and so the final decision made by CNN library. As mentioned before this software also capable do some image processing on scanned paper to lower the final costs.