Our products

DigiPath Viewer

The DigiPath Viewer is a powerful diagnostic support tool that focuses entirely on the pathologist’s workstation and improves laboratory performance in terms of throughput, quality, robustness, and (remote) accessibility. The fully integrated feedback loops improve both human and AI diagnostic performance*.

Request a demo

The most important features of the DigiPath Viewer

Accessible at any time and from any location

Management of the digital workflow

Digital microscope with AI augmentation

Automatic measurement of the morphometry

Structured diagnosis / AI-suggestions

Automatic text report generator

Stylus pen support

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

Semi-automatic
annotation tool

AI Module: Dermatopathology

Our AI model can detect and classify more than 40 skin diseases*. These include high-volume cases such as basal cell carcinoma (BCC) and rare but lethal lesions, e.g. Merkel cell carcinoma and melanoma. Overall, with 40+ diagnoses, we already cover about 80% of routine daily cases in a dermatopathology laboratory, as we observed with our test installations in the pilot laboratories.

The following example shows an interesting case with a melanoma (red, malignant) next to a nevus (blue and pink, benign):

Currently covered AI diagnoses

Basal cell carcinoma
Squamous cell carcinoma
Nevi (4+)
Cysts (3+)
Scar
Merkel cell carcinoma
Angioma

Adnex tumors (15+)
Lentigo solaris
Molluscum contagiosum
Actinic keratosis
Serborrheic keratosis
Bowen’s disease
Histiozytoma

Melanoma
Neurofibroma
Neuroma
Onychomycosis (PAS)
Tinea (PAS)
Psoriasis
Eczema

AI Module: Detection of melanoma metastases

This module is able to detect melanoma metastases from H&E images of lymph node sections. For metastases larger than 0.1 mm in diameter, the method has a very high sensitivity that could be used for quality control or as an additional test*.