In the past three decades, the use of smart methods in medical diagnostic systems has attractedthe attention of many researchers. However, no smart activity has been provided in the eld ofmedical image processing for diagnosis of bladder cancer through cystoscopy images despite the highprevalence in the world. In this paper, two well-known convolutional neural networks (CNNs) ...

image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...

Three dierent methods were investigated to determine their ability to detect and classify various categories of diuse liver disease. A statistical method, i.e., discriminant analysis, a supervised neural network called backpropagation and a nonsupervised, self-organizing feature map were examined. The investigation was performed on the basis of a previously selected set of acoustic and image te...

Interactive unsupervised classication and visualization for browsing an image collection. HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridiscip...

The counting and classification of blood cells allows the evaluation and diagnosis of a vast number of diseases. Through the analysis of white blood cells (WBCs) the ALL Acute Lymphocytic Leukemia, a blood cancer that can be fatal if left untreated, can be detected. Nowadays the morphological analysis of blood cells is performed manually by skilled operators. This involves numerous drawbacks, s...

introduction:in this study, ecg signals have been embedded into medical images to create a novel blind watermarking method. the embedding is done when the original image is compressed using the ezw algorithm. the extraction process is performed at the decompression time of the watermarked image. materials and methods: the multi-resolution watermarking with a secret key algorithm developed in th...

1 Problem Statement In unsupervised classication, we are given a collection of samples and must label them to show their class membership, without knowing anything about the underlying data generating machinery, not even the number of classes. That is, we are given some sequence of observed objects 1; 2 Now we must assign each object to one of a number of classes C = C 1 ; : : : ; C c in an \op...