Publicaties
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Computer aided FCD lesion detection based on T1 MRI data Universiteit Gent
Computer aided diagnosis for suspect keratoconus detection Universiteit Antwerpen Universiteit Hasselt
Purpose: To develop a stable and low-cost computer aided diagnosis (CAD) system for early keratoconus detection for clinical use. Methods: The CAD combines a custom-made mathematical model, a feedforward neural network (FFN) and a Grossberg-Runge Kutta architecture to detect clinical and suspect keratoconus. It was applied to retrospective data of 851 subjects for whom corneal elevation and thickness data was available. These data were divided ...
The Argos project: The development of a computer-aided detection system to improve detection of Barrett's neoplasia on white light endoscopy KU Leuven
BACKGROUND: Computer-aided detection (CAD) systems might assist endoscopists in the recognition of Barrett's neoplasia. AIM: To develop a CAD system using endoscopic images of Barrett's neoplasia. METHODS: White light endoscopy (WLE) overview images of 40 neoplastic Barrett's lesions and 20 non-dysplastic Barret's oesophagus (NDBO) patients were prospectively collected. Experts delineated all neoplastic images.The overlap area of at least four ...
A novel computer-aided lung nodule detection system for CT images Vrije Universiteit Brussel
Purpose: The paper presents a complete computer-aided detection (CAD) system for the detection of lung nodules in computed tomography images. A new mixed feature selection and classification methodology is applied for the first time on a difficult medical image analysis problem. Methods: The CAD system was trained and tested on images from the publicly-available Lung Image Database Consortium (LIDC) on the National Cancer Institute website. The ...
Computer-aided detection of focal bone metastases from whole-body multi-modal MRI Vrije Universiteit Brussel
The confident detection and monitoring of metastatic bone disease remains one of the major unfulfilled needs in oncology. Whole-body MRI offers excellent resolution and sensitivity for the detection of neoplastic cells within the bone marrow using so-called anatomical sequences. In combination with whole-body diffusion-weighted functional sequences, it has shown a great potential in the assessment of patient tumor involvement. However, ...
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge Vrije Universiteit Brussel
Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different systems on a common database. We have therefore set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available ...
Analysis of a Feature-Deselective Neuroevolution Classifier (FD-NEAT) in a Computer-Aided Lung Nodule Detection System for CT Images Vrije Universiteit Brussel
Systems for Computer-Aided Detection (CAD), specifically for lung nodule detection received increasing attention in recent years. This is in tandem with the observation that patients who are diagnosed with early stage lung cancer and who undergo curative resection have a much better prognosis. In this paper, we analyze the performance of a novel feature-deselective neuroevolution method called FD-NEAT to retain relevant features derived from CT ...
Computer-aided detection and segmentation of malignant melanoma lesions on whole-body F-18-FDG PET/CT using an interpretable deep learning approach Interuniversitair Micro-Electronica Centrum vzw Vrije Universiteit Brussel
Background and objective: In oncology, 18-fluorodeoxyglucose (F-18-FDG) positron emission tomography (PET) / computed tomography (CT) is widely used to identify and analyse metabolically-active tumours. The combination of the high sensitivity and specificity from F-18-FDG PET and the high resolution from CT makes accurate assessment of disease status and treatment response possible. Since cancer is a systemic disease, whole-body imaging is of ...