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Multi-photon Imaging of Tumor Cell Invasion in an Orthotopic Mouse Model of Oral Squamous Cell Carcinoma
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Histopathological imaging database for oral cancer analysis.

Tabassum Yesmin Rahman1, Lipi B Mahanta2, Anup K Das3

  • 1Department of Computer Science & IT, Cotton University, Panbazar, Guwahati, Assam, 781001, India.

Data in Brief
|February 6, 2020
PubMed
Summary

This study presents a dataset of 1224 histopathological images of oral cavity normal epithelium and Oral Squamous Cell Carcinoma (OSCC). This resource supports the development of AI-driven diagnostic tools for more objective cancer detection.

Keywords:
100x400xBiopsy slidesHistopathologyOSCCOral cancer

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Area of Science:

  • Pathology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Histopathology is crucial for disease diagnosis, particularly cancer, relying on microscopic examination of tissue biopsies.
  • Current methods using biopsies may lack uniformity and reproducibility due to subjective criteria.
  • Computational tools offer objective, quantitative measures for diagnostic assessments.

Purpose of the Study:

  • To introduce a comprehensive dataset of histopathological images for Oral Squamous Cell Carcinoma (OSCC) research.
  • To facilitate the development of automated diagnostic systems leveraging Artificial Intelligence (AI).

Main Methods:

  • A repository of 1224 H&E stained histopathological images from 230 patients was curated.
  • Images include normal oral epithelium and OSCC at 100x and 400x magnifications.
  • A subset was previously used for OSCC detection based on textural features.

Main Results:

  • The dataset comprises 1224 images, divided into two sets with varying resolutions (100x and 400x).
  • Includes 1080 OSCC images and 290 normal oral epithelium images.
  • The data was collected using a Leica ICC50 HD microscope and prepared by medical experts.

Conclusions:

  • This dataset provides a valuable resource for training and validating AI algorithms for OSCC diagnosis.
  • Enables the creation of objective, reproducible, and potentially more accurate diagnostic tools.
  • Aims to advance computational pathology in oral cancer detection.