Hyperspectral signal processing and analysis applied to histopathological diagnosis

• Grant number: 21/00633-0
• Support Opportunities: Regular Research Grants
• Start date: October 01, 2021
• End date: September 30, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Luciano Bachmann
• Grantee: Luciano Bachmann
• Host Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated researchers: Denise Maria Zezell ; Edson Garcia Soares ; Joaquim Cezar Felipe ; Luiz Carlos Conti de Freitas ; Thiago Martini Pereira
• Associated research grant(s): 24/18004-7 - Spie - Photonics West -2025, AR.EXT

Abstract

The anomalies typification in human tissues, including neoplasms, is usually performed by histological examinations on slides containing biopsies. Research on digital biopsy images has grown rapidly, leveraging the development and improvement of image processing methods specially developed or adapted for this category of images. The hyperspectral signals, obtained using infrared equipment, are characterized by presenting for each pixel of the image a spectrum of absorbance values for the different frequencies, which is sensitive to the characteristics of the underlying tissue. This project aims to investigate and validate the hypothesis that infrared hyperspectral signals can be used to recognize patterns that allow the identification of regions of the slide containing healthy tissue or with abnormal characteristics, especially neoplasms. In order to do this, datasets of hyperspectral signals representing absorbance over a wide range of infrared frequencies, obtained from slides containing samples of healthy tissue and abnormal tissue from different organs, such as thyroid, skin and breast, will be analyzed using deep learning techniques, implemented as classifiers, with which it will be possible to characterize the regions of the slide according to the possible anomalies present. Thus, the proposed method will allow the automatic analysis of biopsies, to make the diagnostic process more accurate and effective. Besides, images obtained from biopsy slides stained with Hematoxylin and Eosin will be processed by computer vision techniques in comparison with the hyperspectral signals approach, in order to detect patterns that are not identifiable by the currently used visual method. (AU)

Scientific publications

(7)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SARDO, ARIANE VENZON NAIA; ANDRADE, MAIRA FRANCO; FIGUEIREDO, ANAELIZA; ROSIN, FLAVIA CRISTINA PERILLO; CORREA, LUCIANA; ZEZELL, DENISE MARIA. Does Photobiomodulation Affects CK10 and CK14 in Oral Mucositis Radioinduced Repair?. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, v. 23, n. 24, p. 9-pg., 2022-12-01. (21/00633-0, 17/50332-0, 13/26113-6)

FAROOQ, SAJID; GERMANO, GLEICE; STANCARI, KLEBER ADRIANI; RAFFAELI, ROCIO; CROCE, MARIA VIRGINIA; CROCE, ADELA E.; ZEZELL, DENISE MARIA; IEEE. A 3D discriminant analysis for Hyperspectral FTIR images. 2023 INTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS, OMN AND SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE, SBFOTON IOPC, v. N/A, p. 2-pg., 2023-01-01. (21/00633-0, 17/50332-0)

PERES, DANIELLA LUMARA; FAROOQ, SAJID; RAFFAELI, ROCIO; CROCE, MARIA VIRGINIA; CROCE, ADELA E.; ZEZELL, DENISE MARIA; IEEE. Identification of basal cell carcinoma skin cancer using FTIR and Machine learning. 2023 INTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS, OMN AND SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE, SBFOTON IOPC, v. N/A, p. 2-pg., 2023-01-01. (21/00633-0, 17/50332-0)

FAROOQ, SAJID; PERES, DANIELLA L. PRIME UMARA; CAIXETA, DOUGLAS CARVALHO; LIMA, CASSIO; DA SILVA, ROBINSON SABINO; ZEZELL, DENISE MARIA; IEEE. Monitoring changes in urine from diabetic rats using ATR-FTIR and Machine Learning. 2023 INTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS, OMN AND SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE, SBFOTON IOPC, v. N/A, p. 2-pg., 2023-01-01. (21/00633-0, 17/50332-0)

OLIVEIRA BAFFA, MATHEUS DE REIMS; BACHMANN, LUCIANO; ZEZELL, DENISE MARIA; PEREIRA, THIAGO MARTINI; DESERNO, THOMAS MARTIN; FELIPE, JOAQUIM CEZAR; ALMEIDA, JR; SPILIOPOULOU, M; ANDRADES, JAB; PLACIDI, G; et al. Advancing Thyroid Pathologies Detection with Recurrent Neural Networks and Micro-FTIR Hyperspectral Imaging. 2023 IEEE 36TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS, v. N/A, p. 5-pg., 2023-01-01. (21/00633-0)

FAROOQ, SAJID; DEL-VALLE, MATHEUS; DOS SANTOS, MOISES OLIVEIRA; DOS SANTOS, SOFIA NASCIMENTO; BERNARDES, EMERSON SOARES; ZEZELL, DENISE MARIA. Rapid identification of breast cancer subtypes using micro-FTIR and machine learning methods. APPLIED OPTICS, v. 62, n. 8, p. 8-pg., 2023-03-10. (21/00633-0, 17/50332-0)

AUGUSTO DE CASTRO, PEDRO ARTHUR; DIAS, DERLY AUGUSTO; DEL-VALLE, MATHEUS; VELOSO, MARCELO NORONHA; RIBEIRO SOMESSARI, ELIZABETH SEBASTIANA; ZEZELL, DENISE MARIA. Assessment of bone dose response using ATR-FTIR spectroscopy: A potential method for biodosimetry. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, v. 273, p. 7-pg., 2022-02-24. (21/00633-0, 17/50332-0)