Surgical Instrument Detection With Computer Vision
Published 6/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 7h 10m | Size: 2.55 GB
Build a Smart AI System to Identify Surgical Tools in Real-Time Using Python, OpenCV, and YOLO
What you'll learn
Master Python from Beginner to Advanced
Implement Image Processing Projects Step-by-Step
Label Images Effectively Using Roboflow
Train YOLO Models for Object Detection
Deep Learning Techniques for Computer Vision
Advanced Image Processing with OpenCV
Build Real-Time Detection Applications
Requirements
Basic Computer Skills - No Prior Coding Required
A PC or Laptop with Internet Access
Python Installed (Setup Guidance Provided)
Interest in Computer Vision and AI
Description
Curious how artificial intelligence is revolutionizing healthcare and medical imaging? Want to build a real-time system that can detect surgical instruments with high precision?Welcome to the project-based course: Surgical Instrument Detection with Computer Vision and Deep Learning.In this hands-on course, you'll learn to create an intelligent system that can identify surgical tools using the power of AI and computer vision. Whether you're in biomedical engineering, AI research, or healthcare innovation, this course gives you the practical tools to bring machine learning into the operating room - virtually.What You Will Learn
ython Programming: Work with the go-to language for AI and machine learning, renowned for its clarity and ecosystem.OpenCV for Image Processing: Dive into real-time image handling, preprocessing, and visualization.YOLOv8 Object Detection: Use the latest version of YOLO (You Only Look Once), one of the fastest and most accurate object detection models.Dataset Preparation: Learn how to gather and annotate images of surgical instruments using tools like Roboflow or CVAT.Model Training and Inference: Train your own custom YOLO model tailored for surgical tool detection.Live and Video Detection: Apply your model on real-time video or surgical footage.Post-Detection Analysis: Measure detection accuracy, track tool usage, and prepare outputs for clinical insights.What You'll Build:A deep learning system capable of recognizing various surgical instruments using only a camera feed.A foundational AI tool useful in smart surgery, tool inventory, or training simulations.A standout portfolio project that demonstrates real-world healthcare AI application.Why Take This Course?Medical Impact: Enter the growing field of AI in healthcare and digital surgery.Hands-On Approach: Learn by doing - minimal theory, maximum implementation.No Special Hardware Needed: Everything runs on a regular laptop with free, open-source tools.Career Booster: Ideal for students, AI enthusiasts, or healthcare tech professionals looking to build applied skills.Whether you're a beginner or an aspiring AI healthcare innovator, this course gives you the skills to combine medical knowledge with cutting-edge vision technology. Make a real difference in how surgeries are monitored, tools are managed, and data is processed - all with the power of deep learning.Important Note:Some of the core tools and workflows used in this course - such as Roboflow, labeling, and model training - may also appear in my other courses.However, each course is built around a completely different dataset, project goal, and real-world application.Even when similar tools are used, the challenges, outcomes, and final use cases are entirely unique in each course.This course is self-contained and designed to deliver a specific learning experience related to its own topic.Who this course is for
Beginners
Students
AI Developers
Aspiring Data Scientists
Beginners in Python
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