CV Lattes
ORCID
Google Scholar Citations
Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. Instituto de Ciência e Tecnologia (ICT) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Graduated and Master in Computer Science from the Federal University of Uberlândia (UFU), and PhD in Information Engineering from the Federal University of ABC (UFABC) by the Center for Mathematics, Computation and Cognition. With experience in the areas of Computer Science and Information Engineering, with emphasis on Digital Image Processing/ Multimedia Processing, she works in the development of Computer-Aided Diagnosis (CAD). She has research carried out and in development for normalization, segmentation, extraction and selection of features, and classification with application in medical images, including histological images stained with hematoxylin-eosin (HE), hematological images and magnetic resonance images. Her research interests are related to medical image processing, including artificial intelligence techniques, machine learning and pattern recognition. She is a member of the Interdisciplinary Laboratory of Image Processing and Analysis (https://lipai.unifesp.br/) and a collaborator of the CodeLab Project (https://www.codelab-unifesp.org/). (Source: Lattes Curriculum)
| News published in Agência FAPESP Newsletter about the researcher |
| More itemsLess items |
| TITULO |
| Articles published in other media outlets ( ): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |
Cancer diagnosis can be confirmed through computational and visual analyses of histological images. However, color variations of these images can harm computational methods' performance. Normalization techniques can be used for correction of these variations caused by the tissue staining process with Hematoxylin-Eosin stain (H&E), commonly used in real clinical practices. Some challenges …
Despite advancements in the field of image analysis, especially through convolutional neural networks (CNN), it is still possible to investigate the discriminative power of hybrid CNN models by considering different forms of image representations, such as those developed to produce visualizations of the neural activation patterns in a CNN. For example, it is possible to use the values fro…
Diagnosis of different types of cancer can be confirmed by analysis of images obtained by tissue samples digitization stained by Hematoxylin-Eosin (H&E). These histological images can be commonly used by scientific research for the proposal of computer systems that aid pathologists. However, the performance of these systems can suffer from the influence of color variations of H&E histolog…
In areas related to histological research, the staining technique of tissues with suspicion of cancer in biopsies is important for confirmation or not of the respective investigated pathology. Staining methods, such as using H&E (Hematoxylin-Eosin) are commonly applied in such laboratory practice. However, there are possibilities of equivocated diagnosis due to differences in sample stain…
In areas related to histological research, the staining technique of tissues with suspicion of cancer in biopsies is important for confirmation or not of the respective investigated pathology. Staining methods, such as using H&E (Hematoxylin-Eosin) are commonly applied in such laboratory practice. However, there are possibilities of equivocated diagnosis due to differences in sample stain…
The increasing incidence of cancer cases promotes scientific investigation of these diseases in different areas of knowledge. The digitization of tissue samples stained with Hematoxylin-Eosin (H&E) allows the obtaining of the so-called histological images, used for the definition of diagnoses and, consequently, for the choice of effective treatments. With these images, computational syste…
| 1 / 1 | Ongoing grants |
| 2 / 2 | Ongoing scholarships in Brazil |
| 3 / 3 | Completed scholarships in Brazil |
| 6 / 6 | All research grants and scholarships |
| Associated processes | |