Search results for "computer-aided diagnosis"
showing 10 items of 23 documents
Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review
2015
Prostate cancer is the second most diagnosed cancer of men all over the world. In the last few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed to improve diagnosis. In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systems have been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field of research for the last 10years. This survey aims to provide a comprehen…
Normalization of T2W-MRI Prostate Images using Rician a priori
2016
International audience; Prostate cancer is reported to be the second most frequently diagnosed cancer of men in the world. In practise, diagnosis can be affected by multiple factors which reduces the chance to detect the potential lesions. In the last decades, new imaging techniques mainly based on MRI are developed in conjunction with Computer-Aided Diagnosis (CAD) systems to help radiologists for such diagnosis. CAD systems are usually designed as a sequential process consisting of four stages: pre-processing, segmentation, registration and classification. As a pre-processing, image normalization is a critical and important step of the chain in order to design a robust classifier and over…
A visual framework to create photorealistic retinal vessels for diagnosis purposes
2020
The methods developed in recent years for synthesising an ocular fundus can be been divided into two main categories. The first category of methods involves the development of an anatomical model of the eye, where artificial images are generated using appropriate parameters for modelling the vascular networks and fundus. The second type of method has been made possible by the development of deep learning techniques and improvements in the performance of hardware (especially graphics cards equipped with a large number of cores). The methodology proposed here to produce high-resolution synthetic fundus images is intended to be an alternative to the increasingly widespread use of generative ad…
Computer-aided diagnosis in digital mammography: comparison of two commercial systems
2014
Aim: Within this work, a comparative analysis of two commercial computer-aided detection or diagnosis (CAD) systems, CyclopusCAD® mammo (v. 6.0) produced by CyclopusCAD Ltd (Palermo, Italy) and SecondLook® (v. 6.1C) produced by iCAD Inc. (OH, USA) is performed by evaluating the results of both systems application on an unique set of mammographic digital images routinely acquired in a hospital structure. Materials & methods: The two CAD systems have been separately applied on a sample set of 126 mammographic digital cases, having been independently diagnosed by two senior radiologists. According to the human diagnosis, the cases in the sample reference set are divided into 61 negatives and 6…
Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project.
2016
International audience; Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of …
Computer-Aided Diagnosis for Prostate Cancer using Multi-Parametric Magnetic Resonance Imaging
2016
Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world.CaP growth is characterized by two main types of evolution: (i) the slow-growing tumours progress slowly and usually remain confined to the prostate gland; (ii) the fast-growing tumours metastasize from prostate gland to other organs, which might lead to incurable diseases.Therefore, early diagnosis and risk assessment play major roles in patient treatment and follow-up.In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis.In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexit…
Computer-Aided Diagnosis System with Backpropagation Artificial Neural Network—Improving Human Readers Performance
2016
This article presents the results of a study into possibility of artificial neural networks (ANNs) to classify cancer changes in mammographic images. Today’s Computer-Aided Detection (CAD) systems cannot detect 100 % of pathological changes. One of the properties of an ANN is generalized information —it can identify not only learned data but also data that is similar to training set. The combination of CAD and ANN could give better result and help radiologists to take the right decision.
Comparative Study of Feature classification Methods for Mass Lesion Recognition in Digitized Mammograms
2007
In this work a comparison of different classification methods for the identification of mass lesions in digitized mammograms is performed. These methods, used in order to develop Computer Aided Detection (CAD) systems, have been implemented in the framework of the MAGIC-5 Collaboration. The system for identification of mass lesions is based on a three-step procedure: a) preprocessing and segmentation, b) region of interest (ROI) searching, c) feature extraction and classification. It was tested on a very large mammographic database (3369 mammographic images from 967 patients). Each ROI is characterized by eight features extracted from a co-occurrence matrix containing spatial statistics inf…
AUTOMATIC RETINA EXUDATES SEGMENTATION WITHOUT A MANUALLY LABELLED TRAINING SET
2011
International audience; Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, two new methods for the detection of exudates are presented. The methods do not require a lesion training set so the need to ground-truth data is avoided with significant time savings and independence from human error. We evaluate our algorithm with a new publicly available dataset from various ethnic groups and levels of DME. Also, we compare our results with two recent exudate segmentation algorithms on the same dataset. In all of …
Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices
2021
Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagnosis and assessment considering the severe effects of mental stress. In contrast to other health-related wearable devices, wearable or portable devices for stress assessment have not been developed yet. A major requirement for the development of such a device is a time-efficient algorithm. This study investigates the performance of computer-aided approaches for mental stress assessment. Machine learning (ML) approaches are compared in terms of the time required for feature extraction and classification. After conducting tests on data for real-t…