Abstract Introduction The number of Alzheimer's Disease (AD) patients is increasing with
increased life expectancy and 115.4 million people are expected to be affected in 2050 …

Medical imaging systems often require the application of image enhancement techniques to
help physicians in anomaly/abnormality detection and diagnosis, as well as to improve the …

We have developed and implemented methods of extracting morphological features from
images of biofilms in order to quantify the characteristics of the inherent heterogeneity. This …

Automatic segmentation of the prostate of and the prostatic zones on MRI remains one of the
most compelling research areas. While different image enhancement techniques are …

Longitudinal MR imaging is increasingly being used to measure cerebral atrophy
progression in dementia and other neurological disorders. Differences in intensity …

In vivo range monitoring techniques are necessary in order to fully take advantage of the
high dose gradients deliverable in hadrontherapy treatments. Positron emission tomography …

Image processing algorithms continue to demand higher performance from computers.
However, computer performance is not improving at the same rate as before. In response to …

In this paper, we present an application of Deep Neural Networks to the detection of Fin
Whales (Balaenoptera physalus) pulses, also known as calls, from very long acoustic …

In the proposed work, a CNN-based Super-Resolution Convolutional Neural Network
(SRCNN) framework for landslide photographs is used for resolution improvement. SRCNN …

This paper presents a robust two-step segmentation procedure for the study of biofilm
structure. Without user intervention, the procedure segments volumetric biofilm images …