Realization of preprocessing blocks of CNN based CASA system on FPGA

Abstract

In this paper, hardware optimization of the preprocessing part of a computer aided semen analysis (CASA) system is proposed, which is also implemented on an FPGA device as a working prototype. A real-time cellular neural network (CNN) emulator (RTCNNP-v2) is used for the realization of the image processing algorithms, whose regular, flexible and reconfigurable infrastructure simplifies the prototyping process. For future work, the post-processing part of the CASA system is proposed to be implemented on the same FPGA device as software, using either a soft or hard processor core. By the integration of the pre-and post-processing parts, the designed CASA system will be capable of processing full-HD 1080p@60 (1080×1920) video images in real-time.

Computer assisted sperm analysis system designed on a hybrid CPU + FPGA architecture

“…Sperm analizi, spermin dinamik özelliklerinin araştırıldığı Motilite Analizi ve yapısal özelliklerinin araştırıldığı Morfoloji Analizi bölümlerinden oluşur [7]. Bu incelemelerin bir standard içinde değerlendirilmesi için Dünya Sağlık Örgütü (WHO) ve Kruger ölçütleri esas alınmaktadır [8], [9].…”

“…Ayrıca spermin izlediği yol için de VCL, VSL, VAP, ALH, BCF, LIN, WOB, STR gibi parametreler istatistik verilerle birlikte belirlenir[7]. Genel olarak doğrusal yörüngeli hızlı sınıfa yani Sınıf I'e giren sperm sayısının çok olması yani spermlerin çoğunlukla sınıf I e girmesi spermlerin sağlıklı olduğunu gösterir.…”

Neural Implementation of Shape-Invariant Touch Counter Based on Euler Calculus

“…Conventionally, perceptrons or similar layered networks have been used as a model of pattern recognition in the brain [7]- [10]. Although perceptron-like machines show invariance to, say, object rotations to some extent, their analogue nature of computation makes it difficult to achieve the invariance with the infinite precision, especially in counting [11], [12].…”