Aristófanes C. Silva

Analysis of spatial variability using geostatistical functions for diagnosis of lung nodule in computerized tomography images

This paper analyzes four geostatistical functions—semivariogram, semimadogram, covariogram, and correlogram—with the purpose of characterizing lung nodules as malignant or benign in computerized tomography images. The tests described in this paper were carried out using a sample of 30 nodules, 24 benign and 6 malignant. Stepwise discriminant analysis was used to determine which combination of measures were best able to discriminate between the benign and malignant nodules. Then, a linear discriminant analysis procedure was performed using the selected features to evaluate the ability of these features to predict the classification for each nodule. A leave-one-out procedure was used to provide a less biased estimate of the linear discriminator’s performance. All analyzed functions have value area under receiver operation characteristic (ROC) curve above 0.800, which means results with accuracy between good and excellent. The preliminary results of this approach are very promising in characterizing nodules using geostatistical functions.

Diagnosis of lung nodule using Gini coefficient and skeletonization in computerized tomography images

This paper uses the Gini coefficient and a set of skeleton measures, with the purposes, with the purpose of characterizing lung nodules as malignant or benign in computerized tomography images.Based on a sample of 31 nodules, 25 benign and 6 malignant, these methods are first analyzed individually and then jointly, with classfication and analysis techniques (linear stepwise discriminant analysis, leave-one-out and ROC curve). We have concluded that the individual measures and their combinations produce good results in the diagnosis of lung nodules.

Analysis of the BRAF V600E mutation in primary cutaneous melanoma.

BRAF V600E is the most common mutation in cutaneous melanomas, and has been described in 30-72% of such cases. This mutation results in the substitution of valine for glutamic acid at position 600 of the BRAF protein, which consequently becomes constitutively activated. The present study investigated the BRAF V600E mutation frequency and its clinical implications in a group of 77 primary cutaneous melanoma patients treated in a cancer reference center in Brazil. Mutation analysis was accomplished by polymerase chain reaction, restriction fragment length polymorphism, and automated DNA sequencing. The chi-squared and Fischer exact tests were used for comparative analyses. The BRAF V600E mutation was detected in 54/77 (70.1%) melanoma subjects. However, no statistically significant association was found between the presence of the mutation and clinical or prognostic parameters. Our results demonstrated that the BRAF V600E mutation is a common event in melanomas, representing an important molecular target for novel therapeutic approaches in such tumors.

DIAGNOSIS OF BREAST REGIONS THROUGH THE USE OF RIPLEY'S K FUNCTION AND SVM

Breast cancer has become increasingly common among the female population over 40 years and is the type of cancer that affects more women worldwide. One way to early detect non-palpable tumors that cause breast cancer is to perform an X-ray (mammogram) of the breasts. It is known that the chances of curing breast cancer is high if detected in early stages. However, the sensitivity of this test may vary widely due to factors such as examination quality or specialist experience. Thus, the use of diagnose systems in order to assist the specialist, have increased the chances of correct diagnoses. This paper presents a methodology for image spatial texture analysis and recognition of patterns present in mass extracted from images of mammograms, according to their malignant or benign behavior. Therefore, this paper uses the Ripley’s K function to extract texture and SVM for pattern recognition. The best result achieved was 85% accuracy, 88.23% sensitivity and 80.76% specificity with Az = 0.84.

Informatics and Computerized Tomography Aiding Detection and Diagnosis of Solitary Lung Cancer

Aristofanes Correa Silva1, Anselmo Cardoso Paiva2, Rodolfo Acatauassu Nunes3 and Marcelo Gattass4 1,2Federal University of Maranhao, Applied Computing Group NCA/UFMA, Av. dos Portugueses, S/N, Campus do Bacanga, Bacanga, CEP 65085-580, Sao Luis MA 3State University of Rio de Janeiro UERJ, Sao Francisco de Xavier, 524, Maracana, CEP 20550-900, Rio de Janeiro, RJ 4Pontiphical Catholic University of Rio de Janeiro PUC-Rio, R. Sao Vicente, 225, Gavea, CEP 22453-900, Rio de Janeiro, RJ Brazil

Diagnosis of lung nodule using the semivariogram function

This paper proposes using the semivariogram function, to help characterize lung nodules as malignant or benign in computerized tomography images.