14 Result(s)
-
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 ...
-
Chapter and Conference Paper
Comparison of MR Preprocessing Strategies and Sequences for Radiomics-Based MGMT Prediction
Hypermethylation of the O6-methylguanine-DNA-methyltransferase (MGMT) promoter in glioblastoma (GBM) is a predictive biomarker associated with improved treatment outcome. In clinical practice, MGMT methylation...
-
Chapter and Conference Paper
Multi-task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer
We propose a novel method for the prediction of patient prognosis with Head and Neck cancer (H&N) from FDG-PET/CT images. In particular, we aim at automatically predicting Disease-Free Survival (DFS) for patie...
-
Chapter and Conference Paper
Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging
Image scale carries crucial information in medical imaging, e.g. the size and spatial frequency of local structures, lesions, tumors and cell nuclei. With feature transfer being a common practice, scale-invari...
-
Chapter and Conference Paper
Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features
We define and investigate the Local Rotation Invariance (LRI) and Directional Sensitivity (DS) of radiomics features. Most of the classical features cannot combine the two properties, which are antagonist in s...
-
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...
-
Chapter and Conference Paper
A Lung Graph–Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images
This article presents a novel graph–model approach encoding the relations between the perfusion in several regions of the lung extracted from a geometry–based atlas. Unlike previous approaches that individuall...
-
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...
-
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 ...
-
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 ...
-
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 ...
-
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...
-
Chapter and Conference Paper
Information Fusion for Combining Visual and Textual Image Retrieval in ImageCLEF@ICPR
In the ImageCLEF image retrieval competition multimodal image retrieval has been evaluated over the past seven years. For ICPR 2010 a contest was organized for the fusion of visual and textual retrieval as thi...
-
Chapter and Conference Paper
Learning a Frequency–Based Weighting for Medical Image Classification
This article describes the use of a frequency–based weighting developed for image retrieval to perform automatic annotation of images (medical and non–medical). The techniques applied are based on a simple tf/idf
