ABOUT MAMMO ASSIST

MammoAssist is an intelligent AI algorithm developed using Deep Learning and Image Processing approach in the field of radiology which analyzes Mammograms for Early Stage Breast Cancer Detection. It identifies critical clinical findings including BI-RADS Categorization in turn enhancing the ability of a radiologist to accurately report cases with High Accuracy and Efficiency. It provides Standard Interface with Healthcare Systems through industry standard protocols as well as it is capable of generating fully automated preliminary analysis report.

DETECTION CAPABILITIES

  • Breast Parenchyma Composition
  • Bilateral Breast Volume
  • Micro & Macro Calcification
  • Clustered Calcification
  • Architectural Distortion
  • Lesion & Lymph Node
  • Shape, Size, Location & Density
  • BI-RADS Categorization

VALUE PROPOSITION

  • Critical Clinical Findings
  • Mass Screening
  • Structured Reporting
  • Increased Productivity
  • Enhanced Accuracy
  • Improved Consistency
  • Automated QA
  • Detailed Preliminary Analysis Report

How MammoAssist Works?

01-01

Service Integration

MammoAssist is capable of integrating and processing any DICOM images and providing annotation for breast cancer detection with a Structured Report. The algorithm and tool can be plugged into any existing radiology workflow (RIS-PACS) and 2D DICOM Viewer. Here is how it works:

  1. DICOM images are received on Telerad Tech’s server
  2. Through service integration, the user runs the AI tools on T2 Medical Image Analytics Platform
  3. The annotation with findings is marked over the images and shown to the end user
  4. The algorithm provides observation results through its structured reporting feature

MammoAssist will benefit

  • Independent Radiologists providing Onsite Read and Tele-reporting Services
  • Radiology and Teleradiology Service Providers
  • Single-site Hospitals and standalone Medical Imaging Centers
  • Medical Imaging Chain dispersed across geography
  • Multi-site, Multi-geography Hospitals
  • Medical Colleges, Universities and Research Institutes
  • Mobile Mammography Unit/ Mobile Breast Cancer Detection Units
  • Mammography Equipment Manufacturers

CALCIFICATION MICRO, MACRO, CLUSTERED

01-01

AI ANALYSIS

Breast Parenchyma Composition: ACR Type 3 (Heterogeneously Dense)
Bilateral Breast Volume: Asymmetric
Calcification: RCC – Clustered Calcification detected at Posterior Medial position measuring 2.368 cm x 1.976 cm LCC – Macro Calcification is detected at Middle Medial position measuring 1.315 cm x 1.002 cm
Lesion: Absent
Architectural Distortion: Absent
ACR BI-RADS Assessment Category – 4 (Suspicious Abnormalities – Biopsy should be Considered)

LESION ANALYSIS

01-02

AI ANALYSIS

Breast Parenchyma Composition: ACR Type 3 (Heterogeneously Dense)
Bilateral Breast Volume: Asymmetric
Calcification: Absent
Lesion: RCC – High Dense Round Lesion detected at Posterior Lateral position measuring 2.755 cm x 2.680 cm RMLO – High Dense Round Lesion detected at Posterior Superior & Posterior Inferior position measuring
3.734 cm x 3.267 cm & 2.755 cm x 2.680 cm respectively
Architectural Distortion: Absent
ACR BI-RADS Assessment Category – 5 (Highly Suggestive of Malignancy – Appropriate Action should be Taken)

BILATERAL ASYMMETRY & ARCHITECTURAL DISTORTION

BREAST PARENCHYMA

SHAPE, SIZE, LOCATION & DENSITY

REQUEST FOR MammoAssist DEMO

Contact Us

Write to Us

Our location

INDIA

TELERAD TECH Private Limited

2nd Floor, Plot No. 7G
Opp. Graphite India, Whitefield
Bengaluru, Karnataka 560048, India

USA

TELERAD TECH U.S.A., Inc.

601 Carlson Pkwy, Suite 1050
Minnetonka, MN 55305

Email Address

Customer Care:
customer.support@teleradtech.com

Sales:
sales@teleradtech.com

Enquiry:
info@teleradtech.com

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