This project intends to improve credibility and save money and time by increasing accuracy in laparoscopic surgeries. The idea is about biometrics for internal organs and the goal of the device is to recognize and identify the complexities (e.g. size and condition) of an organ, very similar to facial recognition software. However this software is applied to human internal organs and tracks them via a video feed in real time like a heart or a liver as they wiggle around.

This idea can potentially be utilized to improve surgery safety for better outcomes and decrease complications in Robotic Assisted Surgeries and decrease guess work and increase accuracy. This device can also enhance the learning experience for aspiring surgeons and make reading of ultrasound imaging easier. Multiple disciplines are involved from human anatomy to computer vision, infrared and ultrasound photography and robotics and machine learning.

Currently each year there are about four thousand surgical never events in United States, these events make up the majority of paid compensations, amassing to 1.5 billion dollars. If we can reduce these events by just one percent with this idea of an organ recognition device, we can shave off 15 million dollars and actually save lives! Furthermore this idea can ultimately be utilized as an important piece of puzzle for autonomous surgery.

Imagine a device designed to confirm surgeons assessments and prevent never events. Incredible amounts of of time, money and legal efforts will be saved if we eliminate adverse and near-miss events. It is natural for patients to experience stress and anxiety while going through complicated health operations. Patients can feel more comfort, knowing an extra safety net exists. For the benefit of the patients, this device is a supplementary assist and will aid surgeons to perform with super confidence in complicated procedures.

About the Author:
After graduating in Industrial and Systems Engineering from University of Southern California, Amir travelled abroad to learn more about the world. During this time he received his MBA. He is now relocated in Los Angeles and looks forward to the bright future of biotechnologies and medical startups in Southern California. After his relocation he has been in contact with prominent labs in USC Keck and UCLA Geffen and sensed an opportunity for computer vision and machine learning in medical and surgical settings.

 

 

MEDICAL IMAGING & BIOMEDICAL DIAGNOSTICS

Author: AmirReza (Ari) Mir

Status: Completed Work