AIDC Summit LA: Wipro Solutions Overview
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Medical images (CT scans, X-Rays) must be segmented to identify the region of interest; then areas of interest must be classified for diagnosis and reporting Applied for Lung Disease diagnosis from Chest X-Rays/CT-Scans Segmentation/classification can be a tedious process. AI can help! Wipro used Deep Learning to develop a Medical Image Segmentation & Diagnosis Solution running on Intel’s AI platform.
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AIDC Summit LA: Wipro Solutions Overview
- 2. Intel Confidential—Subject to NDA 2 • Company overview • Business problems solved • Use of Intel AI technology • Results Agenda Logo here
- 3. Intel Confidential—Subject to NDA 3 Logo here IT Services Revenue in FY 2017-18 Active global clients* Employee Count* Countries with Employee presence* $8.1Bn 1132 57172,379 *Figures based on Q3 2018-19 for Global IT Services business
- 4. Intel Confidential—Subject to NDA 4 AIBuilders:BusinessProblemsSolved Logo here Pipeline Anomalies Surface Cracks Lung Segmentation, Lung Disease Diagnosis External Structural Cracks Inspection Medical Imaging Pipeline Inspection
- 5. Intel Confidential—Subject to NDA 5 Medical Imaging
- 6. Intel Confidential—Subject to NDA 6 Medical images (CT scans, X-Rays) must be segmented to identify the region of interest; then areas of interest must be classified for diagnosis and reporting Applied for Lung Disease diagnosis from Chest X-Rays/CT-Scans Segmentation/classification can be a tedious process AI can help! Wipro used Deep Learning to develop a Medical Image Segmentation & Diagnosis Solution running on Intel’s AI platform Results still must be certified by a Radiologist – enables them to be more productive MedicalImaging–SolutionOverview Logo here
- 7. Intel Confidential—Subject to NDA 7 HW: Intel Xeon Platinum 8153 Skylake Processors SW: Intel® Distribution of OpenVINO™ Toolkit UseofIntel®AITechnology Logo here
- 8. Intel Confidential—Subject to NDA 8 segmentationResults Logo here Input Image Segmentation Output Dataset: X-Rays: OPENi, Shenzhen Hosp. 650+ X-Ray Images + hand-drawn masks (3.6GB +17MB) CT-Scans: 260+ scan images, Manually segmented lungs (135MB + 68MB) Metrics: Inference: Mean IoU: 0.96 Mean DICE: 0.98 Metrics: IOU = Area of Overlap / Area of Union DICE Coefficient = 2 * (A ∩ B) / (A + B)
- 9. Intel Confidential—Subject to NDA 9 ClassificationResults Logo here Example 1 Example 2 Normal 100%Abnormal 91.9% Dataset: X-Rays: OPENi, Shenzhen Hosp. 650+ X-Ray Images (3.6GB) Metrics: Inference: Accuracy: 0.86 F1 Score: 0.82 Metrics: Accuracy = nCorrect/nTotal F1 Score = 2PR/(P+R); where P(precision) = TP/(TP+FP); R(Recall) = TP/(TP+FN)
- 10. Intel Confidential—Subject to NDA 10 SolutionArchitecture-ImageSEGMENTATION Logo here Model Optimizer Inference Engine IR .xml .bin Trained Model Mask Prediction Script Test Image Predicted Mask Processed Image Data Medical Image Segmentation Model (Keras/TF) Model Performance Tuning Unet Network Training Data Preparation/ Preprocessing Medical Images/ CT Scans & Masks Dataset Intel Xeon Processor and OpenVINO Toolkit Data Prep, Pre=processing: Resizing to 224x224, Histogram Equalization, Zooming, Random Rotation
- 11. Intel Confidential—Subject to NDA 11 SolutionArchitecture-ImageClassification Logo here Model Optimizer Inference Engine IR .xml .bin Trained Model Image Prediction Script Test Image Predictions Processed Image Data Medical Image Classification Model (Keras/TF) Model Performance Tuning Inception V3 Network Training Data Preparation/ Preprocessing Labelled Medical Image Dataset Intel Xeon Processor and OpenVINO Toolkit Data Prep, Preprocessing: Resizing to 224x224, Histogram Equalization, Zooming, Random Flip, Random Rotation, Scaling
- 12. Intel Confidential—Subject to NDA 12 DEMO
- 13. Intel Confidential—Subject to NDA 13 Performance Logo here 1.43 0.21 0.00 0.50 1.00 1.50 SecondsperImage Segmentation Inference Benchmark Raw Model OpenVino-Optimized Model 7.25 0.09 0.00 2.00 4.00 6.00 8.00 SecondsperImage Classification Inference Benchmark Raw Model OpenVino-Optimized Model
- 14. Intel Confidential—Subject to NDA 14 Pipeline Anomaly Detection
- 15. Intel Confidential—Subject to NDA 15 PipelineAnomalyDetection Logo here
- 16. Intel Confidential—Subject to NDA 16 PipelineAnomaly-Workflow Expert Workflow prior to Wipro’s Solution Workflow with Wipro’s Solution Pipeline Anomaly Report Rover Video Pipeline Anomaly Report Rover Video Wipro AI Solution + Expert – 1-hour of video = 1-hour of expert viewing time – Not easily scalable – Tedious – 1-hour of video = 10-mins of expert viewing time – Scalable – Not Tedious
- 17. Intel Confidential—Subject to NDA 17 ARchitecture OpenVino
- 18. Intel Confidential—Subject to NDA 18 DEMO
- 19. Intel Confidential—Subject to NDA 19 performance 2.475 1.695 0.409 0.3232 0 0.5 1 1.5 2 2.5 3 Platforms Avg.SecondsperFrame Intel i5 CPU Non-Optimized Intel i5 CPU OpenVino Optimized Intel i7 CPU OpenVino Optimized Nvidia 1080 GPU
- 20. Intel Confidential—Subject to NDA 20 Surface Crack Detection
- 21. Intel Confidential—Subject to NDA 21 ARchitecture Faster R-CNN Annotated Annotated Detector : Faster R-CNN Feature Extractor : ResNet-101 Training Dataset : SDNet2018 Optimization : Intel OpenVino / Distributed TensorFlow Application: High-rise Buildings, Long-Span Bridges, Complex Engg. Structures
- 22. Intel Confidential—Subject to NDA 22 Performance Inference Performance: OpenVINO optimized vs non-optimized on i5 and Xeon
- 23. Intel Confidential—Subject to NDA 23 Contact Logo here Sunil Baliga Director of Sales sunil.baliga@wipro.com Sundar Varadarajan Consulting Partner - AI & ML sundar.varadarajan@wipro.com