AIMC Topic: Algorithms

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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...

Multi-scale Convolutional Neural Networks for Lung Nodule Classification.

Information processing in medical imaging : proceedings of the ... conference
We investigate the problem of diagnostic lung nodule classification using thoracic Computed Tomography (CT) screening. Unlike traditional studies primarily relying on nodule segmentation for regional analysis, we tackle a more challenging problem on ...

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...

Exploitation of Medical Crisp Database for Fuzzy Diagnostic Decision Support Systems.

Studies in health technology and informatics
There are several types of Diagnostic Decision Support Systems (DDSS) but all move towards a common direction: provide assistance to the doctors/clinicians to make the right diagnosis for a specific patient, minimizing as much as possible the needed ...

[Non-destructive detection research for hollow heart of potato based on semi-transmission hyperspectral imaging and SVM].

Guang pu xue yu guang pu fen xi = Guang pu
The quality of potato is directly related to their edible value and industrial value. Hollow heart of potato, as a physiological disease occurred inside the tuber, is difficult to be detected. This paper put forward a non-destructive detection method...

GA-ANFIS Expert System Prototype for Prediction of Dermatological Diseases.

Studies in health technology and informatics
This paper presents novel GA-ANFIS expert system prototype for dermatological disease detection by using dermatological features and diagnoses collected in real conditions. Nine dermatological features are used as inputs to classifiers that are based...

Acquisition of Character Translation Rules for Supporting SNOMED CT Localizations.

Studies in health technology and informatics
Translating huge medical terminologies like SNOMED CT is costly and time consuming. We present a methodology that acquires substring substitution rules for single words, based on the known similarity between medical words and their translations, due ...