34 citations · 60 across the 15 of their papers we have counts for
20 papers
Image-Based Path-Planning for Navigation of Soft-Growing Robots in the Spinal Sub-Arachnoid Space
George Dimas, Panagiotis G. Kalozoumis, Panagiotis Vartholomeos +1
Recently, soft robotic procedures are being developed aiming at achieving targeted minimally invasive operations or drug administration in specific locations in the human body. Acc…
Cross-dataset harmonization for robust endoscopic image analysis
Romil Imtiaz, Dimitris K. Iakovidis
A significant problem in endoscopic image analysis is that the machine learning (ML) models used for this purpose usually underperform when applied on images acquired from endoscop…
Fuzzy Distribution Modeling for Synthetic Tabular Data Generation with Causality Preservation
Michael Vasilakakis, Dimitris K. Iakovidis
Synthetic tabular data generation provides an effective alternative for the training of machine learning models when real-world data is limited or inaccessible. However, the hetero…
Self-Supervised Perceptually Interpretable Monocular Depth Estimation
Zain Ul Abidin, George Dimas, Dimitris K. Iakovidis
Self-supervised monocular depth estimation (MDE) enables depth prediction from monocular images without requiring ground-truth supervision, making it attractive for large-scale and…
Multi-Resolution Feature Fusion U-Net for Magnetic Resonance Imaging Segmentation
Eirini Cholopoulou, Dimitrios E. Diamantis, Dimitris K. Iakovidis
The segmentation of anatomical structures in medical images and particularly in MRI scans, is essential for clinical diagnosis and monitoring disease progression. While Deep Learni…
EndoFSA: Endoscopic Few-Shot Image Generation via Rank-Constrained Parameter Adaptation
Panagiota Gatoula, Grigoris Karypidis, Dimitris K. Iakovidis
WCE produces large-scale gastrointestinal image data yet pathological findings remain significantly underrepresented limiting the generalization performance of deep-learning based…
Confidence-Aware Teacher-Student Distillation for 3D Medical Segmentation
Georgios Triantafyllou, Dimitris K. Iakovidis
Medical image segmentation models typically rely on large amounts of densely annotated volumetric data, limiting their scalability across tasks and imaging modalities. This work ad…
ResNet-50 with Class Reweighting and Anatomy-Guided Temporal Decoding for Gastrointestinal Video Analysis
Romil Imtiaz, Dimitris K. Iakovidis
We developed a multi-label gastrointestinal video analysis pipeline based on a ResNet-50 frame classifier followed by anatomy-guided temporal event decoding. The system predicts 17…
Interpretable Similarity of Synthetic Image Utility
Panagiota Gatoula, George Dimas, Dimitris K. Iakovidis
Synthetic medical image data can unlock the potential of deep learning (DL)-based clinical decision support (CDS) systems through the creation of large scale, privacy-preserving, t…
Multiscale Vector-Quantized Variational Autoencoder for Endoscopic Image Synthesis
Dimitrios E. Diamantis, Dimitris K. Iakovidis
Gastrointestinal (GI) imaging via Wireless Capsule Endoscopy (WCE) generates a large number of images requiring manual screening. Deep learning-based Clinical Decision Support (CDS…
Leveraging Unlabeled Scans for NCCT Image Segmentation in Early Stroke Diagnosis: A Semi-Supervised GAN Approach
Maria Thoma, Michalis A. Savelonas, Dimitris K. Iakovidis
Ischemic stroke is a time-critical medical emergency where rapid diagnosis is essential for improving patient outcomes. Non-contrast computed tomography (NCCT) serves as the frontl…
Clinical Evaluation of Medical Image Synthesis: A Case Study in Wireless Capsule Endoscopy
Panagiota Gatoula, Dimitrios E. Diamantis, Anastasios Koulaouzidis +10
Synthetic Data Generation (SDG) based on Artificial Intelligence (AI) can transform the way clinical medicine is delivered by overcoming privacy barriers that currently render clin…
MeLIAD: Interpretable Few-Shot Anomaly Detection with Metric Learning and Entropy-based Scoring
Eirini Cholopoulou, Dimitris K. Iakovidis
Anomaly detection (AD) plays a pivotal role in multimedia applications for detecting defective products and automating quality inspection. Deep learning (DL) models typically requi…
Soft-Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal
Eirini Cholopoulou, Dimitrios E. Diamantis, Dimitra-Christina C. Koutsiou +1
Effective shadow removal is pivotal in enhancing the visual quality of images in various applications, ranging from computer vision to digital photography. During the last decades…
Intuitionistic Fuzzy Cognitive Maps for Interpretable Image Classification
Georgia Sovatzidi, Michael D. Vasilakakis, Dimitris K. Iakovidis
Several deep learning (DL) approaches have been proposed to deal with image classification tasks. However, despite their effectiveness, they lack interpretability, as they are unab…
This Intestine Does Not Exist: Multiscale Residual Variational Autoencoder for Realistic Wireless Capsule Endoscopy Image Generation
Dimitrios E. Diamantis, Panagiota Gatoula, Anastasios Koulaouzidis +1
Medical image synthesis has emerged as a promising solution to address the limited availability of annotated medical data needed for training machine learning algorithms in the con…
E Pluribus Unum Interpretable Convolutional Neural Networks
George Dimas, Eirini Cholopoulou, Dimitris K. Iakovidis
The adoption of Convolutional Neural Network (CNN) models in high-stake domains is hindered by their inability to meet society's demand for transparency in decision-making. So far,…
Fuzzy Pooling
Dimitrios E. Diamantis, Dimitris K. Iakovidis
Convolutional Neural Networks (CNNs) are artificial learning systems typically based on two operations: convolution, which implements feature extraction through filtering, and pool…
Roadmap on Signal Processing for Next Generation Measurement Systems
D. K. Iakovidis, M. Ooi, Y. C. Kuang +31
Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, image…
SalSum: Saliency-based Video Summarization using Generative Adversarial Networks
George Pantazis, George Dimas, Dimitris K. Iakovidis
The huge amount of video data produced daily by camera-based systems, such as surveilance, medical and telecommunication systems, emerges the need for effective video summarization…