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Development of machine-learning-based techniques for illness and injury detection in medical images

01.03.2019

Clinical decision-support systems are often built by manually gathering, formalising and implementing specialist knowledge. Therefore, they are limited by existing human knowledge concerning modelling clinical conditions, diagnosis and therapy, and can be inaccurate because of variations and complexity inherent to medical data. In order to circumvent these limitations, following an obvious growth of publicly available collections of medical-radiology diagnostic images, machine learning has become an irreplaceable tool for solving various problems concerning radiology image analysis.

The goal of this project is to utilise the strength of contemporary findings in the machine-learning and computer-vision field for building quality models for: 1) automating the process for radius bone fracture detection and localisation from arm radiogram, and; 2) automating the process for early diagnosis of arthritis from multimodal (hyperspectral, thermographic, 3D) scans of patient’s hand. This will be achieved through understanding the process of clinical interpretation in medical diagnostics, developing matching physical models of mentioned phenomena for feature extraction and generating synthetic data, whilst using large collections of labelled data for learning models for tissue localisation/segmentation and detection/classification of said phenomena.

The project is conducted at RITEH.

Duration:
2019–2022
Contributors:
Ivan Štajduhar, Jonatan Lerga, Franko Hržić, Teo Manojlović, Matija Milanič, Dražen Brščić, Damir Miletić
Funded by:
University of Rijeka
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Latest Projects

ABsistemDCiCloud

Machine Learning for Knowledge Transfer in Medical Radiology

Estimating River Discharges in Highly Stratified Estuaries

Multilayer Framework for the Information Spreading Characterization in Social Media during the COVID-19 Crisis (InfoCoV)

European Network for assuring food integrity using non-destructive spectral sensors

Latest Research Papers

Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning

Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes

Coupled encoding methods for antimicrobial peptide prediction: How sensitive is a highly accurate model?

The Choice of Time–Frequency Representations of Non-Stationary Signals Affects Machine Learning Model Accuracy: A Case Study on Earthquake Detection from LEN-DB Data

Improved Parametrized Multiple Window Spectrogram with Application in Ship Navigation Systems

Latest News

Assoc. prof. Jonatan Lerga received the Croatian Academy of Sciences and Arts award

Dr. Sc. Nikola Lopac successfully defended his doctoral dissertation

Presentation at the conference “Digital Innovation and Technology for People”

Assoc. prof. dr. sc. Jonatan Lerga presented AIRI Center at the IEEE Rijeka : Computer Society Congress 2021

Prof. dr. sc. Ana Mestrovic participated at the Panel on perspectives and real-life applications of AI organized by IEEE Technology and Engineering Management Society

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Center for Artificial Intelligence and Cybersecurity
  • jlerga@airi.uniri.hr
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