Releasing the Capabilities of Visual Intelligence™ for Animal Health

Imago Systems, Inc. Visual Intelligence® image of dog heart in pink showing an unmatched level detail.

As in human imaging, Imago’s Visual Intelligence™ platform is ideally suited for Veterinary specialists treating both domesticated and non-domesticated animals, and for food processing industrial applications. Imago is committed to helping improve the quality of animal care and animal food safety and has a dedicated wholly owned subsidiary called Petview Diagnosis (PetViewDX) to serve this market. www.petviewdx.com

Animal imaging of non-domesticated animals such as chickens used in the food processing industry.
Veterinary medicine for companion animals and food processing industrial applications are the first market applications that Imago is pursuing. Imago has adapted its Visual Intelligence ICE™ reveal platform used for the mammography and Cardiovascular imaging in human medicine for animals. The image processing-based algorithms are designed to help clinicians detect and diagnose a variety of veterinary diagnostic Use Cases. We define Use Case simply as an application of the software to improve the ability of the clinician to make a more accurate diagnosis of a particular body part or disease.

The first Use Cases in the veterinary market apply to diagnosis of torn ligament, dog spleen splenic masses, liver masses, soft tissue sarcomas, mast cell metastases, and osteosarcomas. Additional research has begun on application of algorithms for clinical pathology to automatically stage the level of cancer utilizing images acquired using photo microscopy.

Use Cases – Initial Clinical Applications

  • Liver and Splenic Mass – differentiate normal/benign/malignant using ML
  • Intestinal Tissue Thickening – differentiate normal/benign/malignant using ML
  • Soft Tissue Sarcoma & Metastases – detect earlier with more detail from radiograph
  • Tumor Metastases – detect earlier with more detail from (V1 Lung from radiograph)
  • Tumor Changes – progressive/regression during treatment from radiograph using ML
  • Detect full or partial tear of cruciate ligament – from radiograph using ML
  • Osteosarcoma – detect earlier with more detail from radiograph
  • Hemangiosarcoma – detect earlier with more detail from radiograph
  • Lipoma Screening – differentiating benign vs. malignant tumors just under the skin

¹Bold indicates Use Cases Currently in Progress

Future Use Cases: Tissue Characterization & Machine Learning

  • Nasal Cancer Characterization
  • General /Abnormal Characterization
  • Mammary Tumor Characterization
  • General Tumor Margin Characterization
  • Bladder Cancer Characterization
  • Many More