image analysis of kidney biopsies using image –mining framework
Post on 05-Jul-2015
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Visvesvaraya Technological UniversityJnanasangama, Belgaum
Rajiv Gandhi Institute of Technology
Cholanagar, RGC Campus, RT Nagar,
Bangalore, Karnataka 560 032
Technical Seminar 2014Department of
biomedical engineering
Image analysis of kidney biopsies using image –mining framework
D Vinayakam(1rg10bm008)
Content:
Introduction
Image Mining
Need For Implementation
Objective
Block Diagram
INTRODUCTION
Definition Function Location
Causes Symptoms
Definition
Definition
Kidney BiopsyTypes Indications
Contradictions Procedure Complication
Types:
1. Native Renal Biopsy
2. Transplant Renal Biopsy
Indications
1. Haematuria
2. Proteinuria
3. Renal Failure
Contradictions
1. Absolute
2. Relative
Procedure
1. Before Biopsy
2. During Biopsy
3. After Biopsy
Complications
Image Mining
Definition
Process
1. Image Features
2. Function
3. Other Shapes
Colour Shapes Textures
Functions Gabor Functions
Other Shapes
Morphological
Closing
Morphological
Opening
Block Diagram
User Action
Define Image
Processing Task
Select
Workflow
Manageme
nt tool
Select
Operat
ors
Taverna
Rapid minner
Framework automation
Taverna
Image file
Work Flow Inputs
Transform Image
Input (1,n)
Transform Image
Output (1,n)
Encode Byte
Array To Base 64Upload Image
InputUpload Image Output
Convert To
8 Bit
Angiogenesis
Extraction
Adaptive
Threshold
Convert To
Binary
Extract
Features Input
Extract Features
Output
Skeletonize
Image
Image Features Skeletonised Image Initial Image
Get Image URL Input
Get Image URL Output
Get Image URL
2 Input
Get Image URL
2 Output
Work Flow Outputs
2 31
4
56
7
8
9
Rapid minner
Case Study Application
Kidney Biopsy
Image Training Set
Kidney Biopsy
Image Test Set
Segmentation
Squares Feature
Extraction
Ground Truth
Training
Segmentation Segmentation
Squares Feature
Characterization
Morphological
Operator
(Majority Voting)
Non Pathogenic
Glomerulus
Pathogenic
Tubulus
Non Pathogenic
Tubulus
Pathogenic
Glomerulus
Object
Detection
Trained Model
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