1,721,045 research outputs found
Extracting fuzzy classification rules from texture segmented hrct lung images
No full textAutomatic tools for detection and identification of lung and lesion from high-resolution CT (HRCT) are becoming increasingly important both for diagnosis and for delivering high-precision radiation therapy. However, development of robust and interpretable classifiers still presents a challenge especially in case of non-small cell lung carcinoma (NSCLC) patients. In this paper, we have attempted to devise such a classifier by extracting fuzzy rules from texture segmented regions from HRCT images of NSCLC patients. A fuzzy inference system (FIS) has been constructed starting from a feature extraction procedure applied on overlapping regions from the same organs and deriving simple if-then rules so that more linguistically interpretable decisions can be implemented. The proposed method has been tested on 138 regions extracted from CT scan images acquired from patients with lung cancer. Assuming two classes of tissues C1 (healthy tissues) and C2 (lesion) as negative and positive, respectively; preliminary results report an AUC 0.98 for lesions and AUC 0.93 for healthy tissue, with an optimal operating condition related to sensitivity 0.96, and specificity 0.98 for lesions and sensitivity 0.99, and specificity 0.94 for healthy tissue. Finally, the following results have been obtained: false-negative rate (FNR)06 % (C1), FNR 02 % (C2), false-positive rate (FPR) 04 % (C1), FPR 03 % (C2), true-positive rate (TPR) 0.94 %, (C1) and TPR 0.98 % (C2)
Breast masses detection using phase portrait analysis and fuzzy inference systems
No full textPURPOSE: Breast masses exhibit variability in margins, shapes, and dimensions, so their detection is a difficult task in mammographic computer-aided diagnosis. Mass detection is usually a two-step procedure: mass identification and false-positive reduction. A new method to automatically detect mass lesions in mammographic images with tuning according to the breast tissue density was developed and tested. METHODS: A modified phase portrait analysis method was introduced, based on the eigenvalue condition number and an eigenvalue intensity map. The method uses an iterative and tissue density-adaptive segmentation procedure with extraction of geometric features. False-positive reduction is accomplished using a fuzzy inference-based classifier. A leave-one-image-out cross-validation procedure was implemented, and stepwise regression analysis was used to automatically extract an optimal set of features. Testing and validation were performed on two different data sets containing at least one malignant mass D1 (388 images) and D2 (674 images), and a third data set N1 (50 images) was used consisting of normal controls. These three data sets were taken from the Digital Database for Screening Mammography. RESULTS: For sensitivities of 0.9, 0.85, 0.80, and 0.75, the best results on cancer images exhibit an False-Positive per Image (FPpI) equal to 0.6, 0.45, 0.35, and 0.3, respectively, using a Bayes Linear Discriminant Analysis (LDA) classifier and an FPpI of 0.85, 0.7, 0.55, and 0.45 using a fuzzy inference system (FIS) for false-positive reduction. When the algorithm is tested on normal images, an FPpI equal to 0.4, 0.3, 0.25, and 0.2 was observed using LDA and 0.3, 0.25, 0.2, and 0.15 using the FIS. CONCLUSION: A preclinical study of an automatic breast mass detection algorithm provided promising results in terms of sensitivity and low false-positive rate. Further development and clinical testing are justified based on the results
Parallel hardware implementation of RADAR electronics equipment for a LASER inspection system
No full textAn amplitude modulated laser radar has been developed by the Italian Agency for New Technologies, Energy and the Environment for periodic in-vessel inspection in large fusion machines (International Thermonuclear Experimental Reactor). The system is able to obtain a complete three-dimensional mapping of the in-vessel surface. A first digital signal processing system was developed to modulate the laser beam and to detect both the amplitude of the backscattered light and the phase difference between it and the modulation signal. This system is based on commercial digital receiver and parallel digital signal processing boards on a VME bus. It reaches a speed of 100 K measures/s, showing good accuracy and stability. Starting from this, a further development has been done to increase the speed up to 2.328 M measures/s. Reaching the submicrosecond speed was necessary to implement the mathematical algorithm in a highly parallel hardware architecture using a field programmable gate array (FPGA). Based on the good results of the previously developed system, it was decided to maintain the same acquisition front-end though using the last release of analog-to-digital converters, to increase the operating frequency from 80 up to 200 MHz. The software algorithm previously used was completely redesigned and optimized to be used in the FPGA hardware architecture
RAPPRESENTAZIONE DELL'INCERTEZZA DI MISURA, MEDIANTE RANDOM FUZZY VARIABLES, DI DATI ESTRATTI DA ALGORITMI DI STIMA DEL RUMORE APPLICATI AD IMMAGINI RADIOGRAFICHE
No full textReference folding subranging caliper ADC
No full textThe paper presents a reduced ADC architecture obtained by introducing the subranging technique into the scheme of a caliper AD converter. This last converter was already proposed as an application of a theory which describes the comparison between scales having the steps prime each other. This converter architecture drastically reduces the number of the required resistors for a full flash realization. The introduction of the subranging technique into the caliper ADC here presented reduces also the number of the required comparators. The result is a very compact architecture. The paper describes a first intention architecture based on ideal components. An example of SPICE simulation is given
Valutazione dell’incertezza di misura in un sistema fuzzy per la classificazione di microcalcificazioni nella mammografia digitale
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