A5014448875- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
- Lung Cancer Diagnosis and Treatment
- Digital Imaging for Blood Diseases
- Glaucoma and retinal disorders
- Image Retrieval and Classification Techniques
- Infrared Thermography in Medicine
- COVID-19 diagnosis using AI
- Colorectal Cancer Screening and Detection
- Advanced Neural Network Applications
- Medical Imaging and Analysis
- Coffee research and impacts
- Medical Image Segmentation Techniques
- Face and Expression Recognition
- Augmented Reality Applications
- Brain Tumor Detection and Classification
- Growth and nutrition in plants
- Advanced X-ray and CT Imaging
- Geographic Information Systems Studies
- Advanced Image and Video Retrieval Techniques
- Ophthalmology and Eye Disorders
- Face recognition and analysis
- Data Management and Algorithms
- Gene expression and cancer classification
Universidade Federal do Maranhão
2016-2025
Instituto Federal do Maranhão
2018-2022
Universidad Filadelfia de México
2021
Tokyo City University
2021
Tokyo University of Science
2021
University of Crete
2021
FORTH Institute of Computer Science
2021
Computing Center
2020
Universidade Federal Fluminense
2016-2020
Kansas State University
2020
Breast cancer occurs with high frequency among the world's population and its effects impact patients' perception of their own sexuality very personal image. This work presents a computational methodology that helps specialists detect breast masses in mammogram images. The first stage aims to improve consists removing objects outside breast, reducing noise highlighting internal structures breast. Next, cellular neural networks are used segment regions might contain masses. These have shapes...
The precise segmentation of kidneys and kidney tumors can help medical specialists to diagnose diseases improve treatment planning, which is highly required in clinical practice. Manual the extremely time-consuming prone variability between different due their heterogeneity. Because this hard work, computational techniques, such as deep convolutional neural networks, have become popular tasks assist early diagnosis tumors. In study, we propose an automatic method delimit computed tomography...
Lung cancer is a disease with significant prevalence in several countries around the world. Its difficult treatment and rapid progression make mortality rates among people affected by this illness to be very high. Aiming offer computational alternative for helping detection of nodules, serving as second opinion specialists, work proposes totally automatic methodology based on successive refining stages. The automated lung nodules scheme consists six stages: thorax extraction, reconstruction,...
Female breast cancer is a major cause of death in occidental countries. CAD/CADx systems can aidradiologists detection and diagnostic lesions mammograms. In this work, we present methodologyto detect masses from The K-means clustering algorithm used to split the mammogramsin regions. Each region then classified through Support Vector Machine (SVM) as mass or non-massregion. SVM machine-learning method, based on principle structural risk minimization, whichperforms well when applied data...
Breast cancer is the second most common type of in world. Several computer-aided detection and diagnosis systems have been used to assist health experts identify suspicious areas that are difficult perceive with human eye, thus aiding cancer. This work proposes a methodology for discrimination classification regions extracted from mammograms as mass non-mass. The Digital Database Screening Mammography (DDSM) was this acquisition mammograms. taxonomic diversity index (Δ) distinctness (Δ(⁎)),...
The processing of medical image is an important tool to assist in minimizing the degree uncertainty specialist, while providing specialists with additional source detect and diagnosis information. Breast cancer most common type that affects female population around world. It also deadly among women. second all others. examination diagnose breast early mammography. In last decades, computational techniques have been developed purpose automatically detecting structures maybe associated tumors...
At the end of 2019, World Health Organization (WHO) reported pneumonia that started in Wuhan, China, as a global emergency problem. Researchers quickly advanced research to try understand this COVID-19 and sough solutions for front-line professionals fighting fatal disease. One tools aid detection, diagnosis, treatment, prevention disease is computed tomography (CT). CT images provide valuable information on how new affects lungs patients. However, analysis these not trivial, especially when...
Female breast cancer is the major cause of cancer-related deaths in western countries. Efforts computer vision have been made order to help improving diagnostic accuracy by radiologists. In this paper, we present a methodology that uses Moran's index and Geary's coefficient measures tissues extracted from mammogram images. These are used as input features for support vector machine classifier with purpose distinguishing between normal abnormal cases well classifying them into benign...
Road accidents are a worldwide problem, affecting millions of people annually. One way to reduce such is predict risk areas and alert drivers. Advanced research has been carried out on identifying accident-influencing factors potential highway mitigate the number road accidents. Machine learning techniques have used build prediction models using supervised classification based labeled dataset. In this work, we experimented with many machine algorithms discover best classifier for Brazilian...