Titlebook: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011; 14th International C Gabor Fichtinger,Anne Martel,Terry Peters Co

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Classification of Alzheimer’s Disease Using a Self-Smoothing Operatorroved accuracy for Alzheimer’s Disease over Diffusion Maps [2] and a popular metric learning approach [3]. State-of-the-art results are obtained in the classification of 120 brain MRIs from ADNI as normal, mild cognitive impairment, and Alzheimer’s.

micronutrients

Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regr among brain structure, cognition and disease status. Using the imaging and cognition data from Alzheimer’s Disease Neuroimaging Initiative , database, the effectiveness of the proposed method is demonstrated by clearly improved performance on predicting both cognitive scores and disease status.

AMBI

Regularized Tensor Factorization for Multi-Modality Medical Image Classificationted. We have validated our method on a multi-modal longitudinal brain imaging study. We compared this method with a publically available classification software based on SVM that has shown state-of-the-art classification rate in number of publications.

TAP

Detection, Grading and Classification of Coronary Stenoses in Computed Tomography Angiographystep and a lumen cross-section estimation step using random regression forests. We show state-of-the-art performance of our method in experiments conducted on a set of 229 CCTA volumes. With an average processing time of 1.8 seconds per case after centerline extraction, our method is significantly faster than competing approaches.

Bucket

Automatic Region-of-Interest Segmentation and Pathology Detection in Magnetically Guided Capsule Endlgorithm was tested on 300 images of different patients with uniformly distributed occurrences of the target pathologies. We correctly segmented 84.72% of bubble areas. A mean detection rate of 86% for the target pathologies was achieved during a 5-fold leave-one-out cross-validation.

AGATE

Conference proceedings 2011lly selected 251 revised papers from 819 submissions for presentation in three volumes. The third volume includes 82 papers organized in topical sections on computer-aided diagnosis and machine learning, and segmentation.