Image Analysis Software in Pathology

Quantitative image analysis is the key advantage of digital pathology over traditional microscopy. Specialized software automates cell counting, biomarker scoring and morphometry, delivering objective and reproducible results. KombiMED supplies image analysis solutions from leading developers worldwide.

Why Image Analysis?

Traditional assessment of histology slides relies on the pathologist's visual perception, which inevitably introduces subjectivity. Studies show that interobserver variability in Ki-67 assessment reaches 20–30%, and in Gleason grading up to 40% between experts of different levels.

Image analysis software solves this problem:

Objective quantification — automated counting of positive and negative cells with precision to a tenth of a percent
Reproducible results — identical analysis parameters for every slide, eliminating “observer fatigue”
High throughput — processing a full WSI in minutes instead of hours of manual counting
Documentation — a complete analysis record with algorithm parameters for audits and publications

Software Categories

Biomarker Quantification

The main application is the quantitative assessment of immunohistochemical (IHC) markers:

Ki-67 — proliferation index, critical for treatment decisions in breast cancer
PD-L1 (TPS, CPS) — predictive marker for immunotherapy
HER2 — status determination for targeted therapy
ER/PR — hormone receptor status in breast cancer
p53, EGFR, ALK — molecular markers for personalized oncology

Morphometric Analysis

Measurement of the geometric parameters of structures: gland area, epithelial thickness, intercellular distances, karyotype index. Used in nephropathology, dermatopathology and neuropathology.

Tissue Segmentation

Automated division of the image into functional zones: tumor, stroma, necrosis, adipose tissue and normal parenchyma. Required for calculating the percentage of tumor tissue and invasion zones.

Cell Population Analysis

Classification and counting of different cell types: lymphocytes (TILs), plasma cells, neutrophils and macrophages. Critical for assessing the tumor immune microenvironment.

Leading Software Solutions

Visiopharm Diagnostic Apps

A platform with a suite of CE-IVD certified applications for biomarker analysis. Its modular architecture allows new markers to be added without replacing the system. AI-assisted segmentation and quantification.

Indica Labs HALO / HALO AI

A powerful quantitative analysis platform with an extensive algorithm library: tissue classification, analysis of spatial relationships between cells (spatial biology), and multiplex IHC and IF analysis.

QuPath

Open-source software for the quantitative analysis of biomedical images. It supports WSI and offers a user-friendly annotation interface and built-in machine learning algorithms. An ideal tool for research laboratories.

Cellpose

A general-purpose deep learning model for cell segmentation. It works with various image types: histology, cytology, fluorescence and phase contrast. Open source.

TIAToolbox

A toolkit for histology image analysis developed at the University of Warwick. It includes pretrained models for tissue classification, nucleus detection and molecular profile prediction.

Cytomine

An open-source web platform for collaborative work with gigapixel images. It allows several researchers to annotate, analyze and share results simultaneously. Built-in machine learning algorithms for automated object detection and classification.

Slideflow

A deep learning framework for WSI analysis. It provides tools for training models on histology data, feature extraction and prediction of clinical outcomes. Supports integration with TensorFlow and PyTorch.

Advantages of Software-Based Analysis

Algorithms deliver a quantitative result without subjective judgment — especially critical for borderline cases (Ki-67 14% vs 16%, HER2 2+).

A complete WSI analysis — tissue segmentation, cell detection and marker counting — takes 2–5 minutes.

Identical algorithm settings make results comparable across laboratories and time points.

Analysis results are automatically added to the pathology report and transferred to the LIS.

Modern platforms analyze not only the number of cells but also their spatial arrangement — key information for immuno-oncology.

Accuracy and objectivity
Processing speed
Protocol standardization
Integration into the clinical workflow
Spatial analysis (spatial biology)

Image Analysis Workflow

1. Scanning — the histology slide is scanned on a WSI scanner

2. Upload to the IMS — the image is transferred to the image management system

3. Selecting the analysis area — the pathologist annotates the region of interest or runs the analysis on the entire slide

4. Running the algorithm — the software performs segmentation, detection and quantification

5. Verifying the results — the pathologist reviews the results and adjusts the region if needed

6. Generating the report — the data are integrated into the pathology report

KombiMED Solutions

KombiMED supports the implementation of image analysis software solutions:

Request a consultation — we will select the optimal set of image analysis tools for your clinical and research needs.

All software solutions integrate with hardware from the KombiMED catalog — slide scanners, microscopes and imaging systems — creating a single, consistent ecosystem for your laboratory.

*KombiMED — centralized procurement of medical equipment from Europe. Deliveries to Kazakhstan, Central Asia and the Caucasus.*

Platform selection to match the laboratory's focus: clinical diagnostics or research
Configuration and validation of algorithms for your staining protocols
Integration with existing scanners and IMS
Training for pathologists and laboratory technicians
Technical support and updates to the algorithm library