In this work we analyze the impact of denoising, contrast and edge enhancement using the
Deceived Non Local Means (DNLM) filter in a Convolutional Neural Network (CNN) based …

Cell instance segmentation in fluorescence microscopy images is becoming essential for
cancer dynamics and prognosis. Data extracted from cancer dynamics allows to understand …

In this work we explore a set of image enhancement techniques for improving contrast and
removing noise from digital images of cell activity. The cells studied were extracted from …

This paper presents a novel computational optimization of the deceived non local means
filter using moving average and symmetric weighting. The proposed optimization is …

In this paper we propose an efficient implementation of the Deceived Non Local Means filter,
using Integral Images and the Fast Fourier Transform, named DNLM-IFFT. The deceived …

In this paper a workflow to extract cell features from brightfield microscopy image sequences
is proposed. An event driven approach, combined with a forward and backward tracking …

Actualmente en el área microbiológica, las metodologıas utilizadas para la identificación de
células cancerıgenas han ido evolucionando debido a la inserción tecnológica en cuanto a …

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of
devices. In this context, there is increasing interest in removing various kinds of noise arising …

현대 사회는 4 차 산업혁명의 영향에 의해 다양한 디지털 통신 장비가 사용되고 있다. 이에 따라
데이터 전송 과정에서 발생하는 잡음제거에 관심이 높아지고 있으며, 효율적으로 영상을 …

In our in vitro study to model and understand the regulation networks that control the live and
death of the cells, it is fundamental to quantify the contribution of each of the cancer …