Tissue Characterization by Image Analysis for Diagnostic Purposes

Tissue Characterization by Image Analysis for Diagnostic Purposes João Sanches jmrs@ist. utl. pt Institute for Systems and Robotics Instituto Superior Técnico

Noise • Different Biomedical Image Modalities present different types of noise, e. g. , additive or multiplicative. • Usually, the noise should be removed. MRI LSFCM CT US

Speckle • Ultrasound images usually present low quality (low SNR) • Images are corrupted by speckle noise (multiplicative) Processed by José Seabra (Biomedical Ph. D student)

Medical Information However, the speckle pattern contains relevant medical information, e. g. , fatty Liver.

Goal • Decompose the image in textural and anatomical/morphological components. • Characterize the texture/“noise” (speckle) • Associate the texture characteristics with the disease. • Classification and Quantification to Detect (Diagnosis) and Quantify (Severity Assessment) the disease.

Decomposition Noisy Synthetic Image Noiseless Image Noise Field

Classification Ultrasound Image Denoising Noise estimation Intensity and anatomical features Textural features Tissue characterization and Diagnosis

Decomposition Examples

“Noise” Analysis for Diagnostic Purposes Two Cases • Liver Steatosis • Atherosclerotic Plaques (carotids and coronaries)

Steatosis • Steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles (genetic, alcohol and obesity) • Today, the assessment is subjectively performed by visual inspection

Steatosis • Comparison with histological data

Steatosis Characterization • Intensity Decay (m) • Texture (Ev, Eh)

Diagnosis Processed by Ricardo Ribeiro (Biomedical Ph. D student)

Atherosclerotic Plaques

3 D Diagnosis Global and local analysis

IVUS

IVUS Collaboration with the Centre de Visió per Computador, Universitat Autònoma de Barcelona, Profª Petia Radeva

IVUS Image decomposition

IVUS Automatic classification GT

Present and Future Work • New texture characterization and classification methods • Aterosclerotic plaques: 3 D Extension of the IVUS • Liver steatosis quantification with additional information from laboratorial analysis data.