| Company Name | Visiopharm |
| Founded | 2001 |
| Head office | Hoersholm, Denmark |
| Website | https://visiopharm.com |
| Contact |
Products by Visiopharm
Subspeciality: Multiple
Modality: Histopathology
Source: Vendor
Measurement of the largest metastasis, Metastasis detection in lymph nodes (H&E)
Visiopharm has developed an AI deep learning application that has been trained to detect metastases in H&E stained lymph nodes associated with breast and colorectal adenocarcinoma. This APP enables pathologists to not only detect areas of metastases in lymph nodes. It also measures and orders metastases based on relevant features for either breast or colorectal cancer metastasis (largest metastasis diameter or total area of metastasis).
Subspeciality: Breast pathology
Modality: Histopathology
Source:
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:
No key features available
Developed for tumor detection in PCK stained breast tissue
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: 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: 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: 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
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.