Search results for "Medical image"

Deep Learning Architectures for Diagnosis of Diabetic Retinopathy

2023

For many years, convolutional neural networks dominated the field of computer vision, not least in the medical field, where problems such as image segmentation were addressed by such networks as the U-Net. The arrival of self-attention-based networks to the field of computer vision through ViTs seems to have changed the trend of using standard convolutions. Throughout this work, we apply different architectures such as U-Net, ViTs and ConvMixer, to compare their performance on a medical semantic segmentation problem. All the models have been trained from scratch on the DRIVE dataset and evaluated on their private counterparts to assess which of the models performed better in the segmentatio…

A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR

2009

With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based descript…

Fuzzy C-Means Inspired Free Form Deformation Technique for Registration

2009

This paper presents a novel method aimed to free form deformation function approximation for purpose of image registration. The method is currently feature-based. The algorithm is inspired to concepts derived from Fuzzy C-means clustering technique such as membership degree and cluster centroids. After algorithm explanation, tests and relative results obtained are presented and discussed. Finally, considerations on future improvements are elucidated.

Computer-Assisted Approaches for Uterine Fibroid Segmentation in MRgFUS Treatments: Quantitative Evaluation and Clinical Feasibility Analysis

2019

Nowadays, uterine fibroids can be treated using Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS), which is a non-invasive therapy exploiting thermal ablation. In order to measure the Non-Perfused Volume (NPV) for treatment response assessment, the ablated fibroid areas (i.e., Region of Treatment, ROT) are manually contoured by a radiologist. The current operator-dependent methodology could affect the subsequent follow-up phases, due to the lack of result repeatability. In addition, this fully manual procedure is time-consuming, considerably increasing execution times. These critical issues can be addressed only by means of accurate and efficient automated Pattern Recognition ap…

A text based indexing system for mammographic image retrieval and classification

2014

Abstract In modern medical systems huge amount of text, words, images and videos are produced and stored in ad hoc databases. Medical community needs to extract precise information from that large amount of data. Currently ICT approaches do not provide a methodology for content-based medical images retrieval and classification. On the other hand, from the Internet of Things (IoT) perspective, the ICT medical data can be produced by several devices. Produced data complies with all Big Data features and constraints. The IoT guidelines put at the center of the system a new smart software to manage and transform Big Data in a new understanding form. This paper describes a text based indexing sy…

Frequency Determined Homomorphic Unsharp Masking Algorithm on Knee MR Images

2005

A very important artifact corrupting Magnetic Resonance (MR) Images is the RF inhomogeneity, also called Bias artifact. The visual effect produced by this kind of artifact is an illumination variation which afflicts this kind of medical images. In literature a lot of works oriented to the suppression of this artifact can be found. The approaches based on homomorphic filtering offer an easy way to perform bias correction but none of them can automatically determine the cut-off frequency. In this work we present a measure based on information theory in order to find the frequency mentioned above and this technique is applied to MR images of the knee which are hardly bias corrupted.

The unnecessary image

2014

A Digital Watermarking Algorithm Based on DCT: Application on Medical Image

2012

International audience; This work is a presentation of a new approach of robust watermarking applied in medical domain such as telemedicine hence the need to keep the visual aspect of medical images and other conservation of the various data substituted. For hiding information, the proposed method uses the Discrete Cosine Transform (DCT) space. To control identification and eventually the correction (if possible) of the data inserted, it should be noted that we used the series turbocode to recover the data inserted and after application of several attacks.

A Watermarking of Medical Image : New Approach Based On "Multi-Layer" Method

2011

In order to contribute to security sharing and transmission of medical images, this paper propose a new approach for Watermarking image based on the techniques of Code Division Multiple Access (CDMA), Discrete Wavelet transform (DWT) and Error Correcting Code (ECC). The motivation of this approach is to improve the quantity of data integration with the conservation of the image visual quality. Therefore, this work permits to the user the capacity to correct the possible alterations if it exists. IRM and Echographic medical image are used to experiment this approach.

Automated segmentation and description of the internal morphology of human permanent teeth by means of micro-CT

2020

High-resolution micro-computed tomography is a powerful tool to analyze and visualize the internal morphology of human permanent teeth. It is increasingly used for investigation of epidemiological questions to provide the dentist with the necessary information required for successful endodontic treatment. The aim of the present paper was to propose an image processing method to automate parts of the work needed to fully describe the internal morphology of human permanent teeth. One hundred and four human teeth were scanned on a high-resolution micro-CT scanner using an automatic specimen changer. Python code in a Jupyter notebook was used to verify and process the scans, prepare the dataset…