Frida

Frida analyzes tissue microarray images to quantify protein expression and perform quantitative histological image analysis for biomedical research.

Key Features:

• Image analysis for tissue microarrays: Analyzes complex image datasets derived from tissue microarrays to quantify protein expression within tissue samples.
• ImageJ integration: Leverages NIH ImageJ functionality for image segmentation, feature extraction, and quantitative analysis.
• Implementation: Implemented in Java and interoperates with ImageJ-based functions.
• Customization: Provides customizable features to develop tailored workflows for different tissue analyses.

Scientific Applications:

• Cancer research: Quantifies protein expression in tissue microarrays to support studies of oncogenic proteins such as the MYC onco-protein.
• Prostate cancer staging and comparison: Analyzes tissue microarrays containing normal tissue, atrophic samples, prostatic intraepithelial neoplasia (PIN), primary adenocarcinoma, and metastatic adenocarcinoma to assess expression differences.
• MYC localization and overexpression analysis: Facilitates identification of nuclear overexpression of MYC in luminal cells across PIN and stages of prostate cancer to investigate early oncogenic events in initiation and progression.

Methodology:

Implements ImageJ-based image segmentation, feature extraction, and quantitative analysis workflows and is implemented in Java.