Find the artificial intelligence based software for pathology that you are looking for. All products listed are available for the European market (CE-IVD marked).
The data presented in the pathology domain is under a publication embargo until May 2026 and should not be used for publication purposes until the embargo period has ended.
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Subspeciality: Hematopathology
Modality: Cytopathology
Source: Public
No key features available
Morphogo is a fully automated bone marrow cell morphology analysis system.
Subspeciality: Breast pathology
Modality: Histopathology
Source: Public
No key features available
No description available
Subspeciality: Breast pathology
Modality: Histopathology
Source:
Subspeciality: Urologic cytopathology
Modality: Cytopathology
Source: Vendor
Atypia scoring, Bladder cancer detection, Follow-up analysis, High grade/Low grade differentiation, Primary diagnosis
VisioCyt® Bladder is an AI-powered, solution designed to diagnose urothelial bladder carcinoma. By analyzing digital urine cytology, the device detects the presence of tumor cells based on their morphological atypia to predict the presence or absence of bladder cancer, and when applicable, an assessment of the tumour grade (high or low). VisioCyt® Bladder is intended to assist its prescribers in the diagnosis of patients exhibiting symptoms suggestive of bladder cancer or for individuals under surveillance for urothelial carcinoma.
Subspeciality: Breast pathology
Modality: Histopathology
Source: Public
ASCO/CAP HER2 IHC guidelines, HER2 Cell-based Scoring
The Human Epidermal Growth Factor Receptor 2 (HER2) is a central biomarker in invasive breast cancer, and the HER2 status is predictive of the patient’s response to HER2-targeted treatment. According to the guidelines of the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP), the HER2 status must be determined by protein expression and/or genetic analysis of breast tissue sections using immunohistochemistry (IHC) and/or in situ hybridization (ISH), respectively. The present protocol is a fully automatic single-cell approach for HER2 IHC quantification that follows ASCO/CAP guidelines, designed with this new scoring regime in mind, i.e. HER2-low and HER2-ultra. It is also configurable to national modifications.
Subspeciality: Breast pathology
Modality: Histopathology
Source: Vendor
fully automated tissue and tumor detection, Nuclei detection inside the invasive tissue, Quantification of positive vs negative nuclei
Fully automated quantification of positively and negatively stained tumor cells in whole slide images stained with progesterone receptor IHC
Subspeciality: Breast pathology
Modality: Histopathology
Source: Vendor
fully automated tissue and tumor detection, Nuclei detection inside the invasive tissue, Quantification of positive vs negative nuclei
Fully automated quantification of positively and negatively stained tumor cells in whole slide images stained with estrogen receptor IHC
Subspeciality: Pulmonary pathology
Modality: Histopathology
Source: Vendor
calculation of the TPS (%), Cell detection inside the invasive tissue, fully automated tissue and tumor detection, Quantification of positive vs negative cells
Fully automated quantification of positively and negatively stained tumor cells in whole slide images stained with PD-L1 IHC and calculation of the Tumor Proportion Score (TPS).
Subspeciality: Breast pathology
Modality: Histopathology
Source:
No key features available
The “Invasive Tumor Detection (VDS)” APP provide means for distinguishing between invasive tumor and non-invasive tumor based on two serial single-stained slides with the myoepithelial cell nuclear marker p63 in one slide and a cytokeratin (CK) tumor marker, e.g. PCK, in another slide. With VirtualDoubleStaining™ the two slides are combined to include invasive tumor structures and exclude non-invasive tumor structures.
Subspeciality: Breast pathology
Modality: Histopathology
Source:
Subspeciality: Breast pathology
Modality: Histopathology
Source: Vendor
Calculation of the proliferation index, Counting of all tumor cells, Counting of positively stained tumor cells
Our Ki-67 solution for breast cancer is fully automated and does not require manual input during analysis. The solution consists of four automated analysis steps. Once started, it automatically separates the sample tissue from control tissues and robustly identifies invasive cancer areas in the sample. Tumor nuclei are counted based on their Ki-67 expression and the resulting proliferation index for the whole tumor area is calculated.
Subspeciality: Infectious disease cytopathology
Modality: Cytopathology
Source:
