Case Study

AI-Powered Image Analysis for Early Detection of Renal Tumors

Empowering a Laboratory and Imaging Services Provider with AI Technologies to Transform Renal Imaging Analysis

A diagnostic imaging services provider empowers its radiologists to enhance diagnostic accuracy and efficiency in the detection of renal tumors by adopting an AI-powered image analysis solution.
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Industry & Region: Healthcare, US
Tech Stack & Techniques:
AI Framework: TensorFlow, Keras, PyTorch, Computer Vision Tools: Faster RCNN, Style GAN Labelling, OpenCV, YOLO, Scripting & Other Tools: Python, NumPy, Annotation Tools, Data Augmentation
Client Overview
Our client is a US-based diagnostics chain offering specialized services such as advanced renal imaging in the renal disease diagnosis segment through the adoption of next-gen technologies.
Business Challenge
Our client was using a legacy solution for the detection of renal tumors in MRI scans. This solution primarily relied on the manual interpretation of MRI scans by radiologists, which was time-consuming and susceptible to human error. Early detection of renal tumors in MRI scans was crucial for improved patient outcomes, prompting the necessity for a more advanced diagnostic approach.
Solution Offered
KANINI was chosen for its expertise in offering tailored AI and machine learning solutions for healthcare and its track record of successful AI implementations, particularly in the renal care segment.
We built and deployed an AI system to automate the identification and characterization of renal tumors in MRI scans. This system utilizes a computer vision model developed using PyTorch, TensorFlow, and OpenCV libraries. The model functions as an object recognition tool specifically designed to identify potential tumors.
Challenges such as data quality issues and algorithm refinement that came up during project delivery were successfully addressed through iterative development cycles and continuous feedback from medical experts.
Close collaboration between KANINI’s AI experts and the client’s medical and IT teams ensured the successful integration and deployment of the AI-powered image analysis solution.
Cutting-edge machine learning algorithms, data preprocessing techniques, and rigorous testing protocols marked the success of the project. Our solution aligned with the client’s commitment to innovation and patient care, enhancing their reputation and competitiveness in the healthcare sector.
Value Delivered
  • Reduced diagnosis turnaround time significantly.
  • Increased tumor detection sensitivity.
  • Minimized dependency on manual interpretation.
  • Enhanced overall patient outcomes through timely intervention.
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AI-Powered Image Analysis for Early Detection of Renal Tumors