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ES

Emet Surgical, Inc

Emet Surgical develops the Enhanced Surgical Precision (ESP) system, a 3D mapping and AI-guided visualization tool that enhances real-time anatomical mapping during robot-assisted and laparoscopic cancer surgeries. This technology improves cancerous tissue identification and reduces reoperation rates by facilitating intraoperative frozen section exams without requiring additional training for surgeons.

Denver, United StatesFounded 20213200+ followers
Updated 4 months ago

Funding

$300K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

During robot-assisted and laparoscopic cancer surgeries, precise identification of cancerous tissue can be challenging, potentially leading to incomplete resections and increased reoperation rates. Current methods for intraoperative assessment may require additional training and can be time-consuming, impacting surgical workflow.

Solution

Emet Surgical's Enhanced Surgical Precision (ESP) system is an augmented intelligence platform designed to improve visualization and anatomical mapping during minimally invasive surgeries. By analyzing the surgical video feed in real-time, ESP generates a dynamic map that highlights anatomical features directly on the surgeon's video display. The system's cancerous tissue recognition engine compares video images to a database of cancerous images, alerting the surgeon to suspicious areas. This "Gross Exam in the OR" approach aims to improve cancerous tissue identification, reduce reoperation rates, and enhance surgical outcomes without requiring extensive additional training.

Target Audience

The primary target audience includes surgeons specializing in robot-assisted and laparoscopic cancer surgeries, as well as hospitals and surgical centers seeking to improve surgical precision and reduce reoperation rates.

Features

  • Real-time dynamic mapping of anatomical features overlaid on the surgical video feed.
  • Cancerous tissue recognition engine that compares video images to a cancerous image database.
  • Alerts to surgeons regarding suspicious areas identified by the AI.
  • Designed for ease of use with existing surgical tools and workflows, minimizing the need for additional training.
  • Aims to facilitate intraoperative frozen section exams.
This profile is AI-generated and may contain inaccuracies.