AIMC Topic: Image Interpretation, Computer-Assisted

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Proposal of Local Automatic Weighing Attribute in CBIR.

Studies in health technology and informatics
Lung cancer is the most common malignant lesion and the principal cause of cancer-related death worldwide. This problem encourages researchers to build computer-aided solutions to help diagnose lung cancer. Content-based image retrieval (CBIR) system...

Thermal Signal Analysis for Breast Cancer Risk Verification.

Studies in health technology and informatics
Breast cancer is the second most common cancer in the world. Currently, there are no effective methods to prevent this disease. However, early diagnosis increases chances of remission. Breast thermography is an option to be considered in screening st...

A Cloud-Based Infrastructure for Feedback-Driven Training and Image Recognition.

Studies in health technology and informatics
Advanced techniques in machine learning combined with scalable "cloud" computing infrastructure are driving the creation of new and innovative health diagnostic applications. We describe a service and application for performing image training and rec...

Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration.

Information processing in medical imaging : proceedings of the ... conference
This paper presents a dictionary learning-based method to segment the brain surface in post-surgical CT images of epilepsy patients following surgical implantation of electrodes. Using the electrodes identified in the post-implantation CT, surgeons r...

Finding a Path for Segmentation Through Sequential Learning.

Information processing in medical imaging : proceedings of the ... conference
Sequential learning techniques, such as auto-context, that applies the output of an intermediate classifier as contextual features for its subsequent classifier has shown impressive performance for semantic segmentation. We show that these methods ca...

Bodypart Recognition Using Multi-stage Deep Learning.

Information processing in medical imaging : proceedings of the ... conference
Automatic medical image analysis systems often start from identifying the human body part contained in the image; Specifically, given a transversal slice, it is important to know which body part it comes from, namely "slice-based bodypart recognition...

Predicting Semantic Descriptions from Medical Images with Convolutional Neural Networks.

Information processing in medical imaging : proceedings of the ... conference
Learning representative computational models from medical imaging data requires large training data sets. Often, voxel-level annotation is unfeasible for sufficient amounts of data. An alternative to manual annotation, is to use the enormous amount o...

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

Information processing in medical imaging : proceedings of the ... conference
Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optim...

A recommender system for medical imaging diagnostic.

Studies in health technology and informatics
The large volume of data captured daily in healthcare institutions is opening new and great perspectives about the best ways to use it towards improving clinical practice. In this paper we present a context-based recommender system to support medical...

Multiple hypotheses image segmentation and classification with application to dietary assessment.

IEEE journal of biomedical and health informatics
We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned...