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Article
Open AccessComparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction
Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MP...
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Article
Open AccessA global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences
Since its emergence in the 1960s, Artificial Intelligence (AI) has grown to conquer many technology products and their fields of application. Machine learning, as a major part of the current AI solutions, can ...
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Article
Open AccessQuantImage v2: a comprehensive and integrated physician-centered cloud platform for radiomics and machine learning research
Radiomics, the field of image-based computational medical biomarker research, has experienced rapid growth over the past decade due to its potential to revolutionize the development of personalized decision su...
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Article
Open AccessReproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT
Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [18F]-FDG has shown superior diagnostic perf...
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Article
Open AccessAssessing radiomics feature stability with simulated CT acquisitions
Medical imaging quantitative features had once disputable usefulness in clinical studies. Nowadays, advancements in analysis techniques, for instance through machine learning, have enabled quantitative feature...
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Article
Open AccessThe importance of feature aggregation in radiomics: a head and neck cancer study
In standard radiomics studies the features extracted from clinical images are mostly quantified with simple statistics such as the average or variance per Region of Interest (ROI). Such approaches may smooth o...
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Article
Open AccessIntegrating radiomics into holomics for personalised oncology: from algorithms to bedside
Radiomics, artificial intelligence, and deep learning figure amongst recent buzzwords in current medical imaging research and technological development. Analysis of medical big data in assessment and follow-up...
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Article
Open AccessRevealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness
We propose an approach for characterizing structural heterogeneity of lung cancer nodules using Computed Tomography Texture Analysis (CTTA). Measures of heterogeneity were used to test the hypothesis that hete...
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Chapter and Conference Paper
Holographic Visualisation and Interaction of Fused CT, PET and MRI Volumetric Medical Imaging Data Using Dedicated Remote GPGPU Ray Casting
Medical experts commonly use imaging including Computed Tomography (CT), Positron-Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) for diagnosis or to plan a surgery. These scans give a highly de...
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Chapter
Text- and Content-Based Medical Image Retrieval in the VISCERAL Retrieval Benchmark
Text- and content-based retrieval are the most widely used approaches for medical image retrieval. They capture the similarity between the images from different perspectives: text-based methods rely on manual ...
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Chapter and Conference Paper
Multidimensional Texture Analysis for Improved Prediction of Ultrasound Liver Tumor Response to Chemotherapy Treatment
The number density of scatterers in tumor tissue contribute to a heterogeneous ultrasound speckle pattern that can be difficult to discern by visual observation. Such tumor stochastic behavior becomes even mor...
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Chapter and Conference Paper
Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma
Medulloblastoma (MB) is a type of brain cancer that represent roughly 25% of all brain tumors in children. In the anaplastic medulloblastoma subtype, it is important to identify the degree of irregularity and ...
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Chapter and Conference Paper
Epileptogenic Lesion Quantification in MRI Using Contralateral 3D Texture Comparisons
Epilepsy is a disorder of the brain that can lead to acute crisis and temporary loss of brain functions. Surgery is used to remove focal lesions that remain resistant to treatment. An accurate localization of ...
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Chapter and Conference Paper
Multiscale Lung Texture Signature Learning Using the Riesz Transform
Texture–based computerized analysis of high–resolution computed tomography images from patients with interstitial lung diseases is introduced to assist radiologists in image interpretation. The cornerstone of ...
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Chapter and Conference Paper
Lung Texture Classification Using Locally–Oriented Riesz Components
We develop a texture analysis framework to assist radiologists in interpreting high–resolution computed tomography (HRCT) images of the lungs of patients affected with interstitial lung diseases (ILD). Novel t...
