SPECT

Explainable AI Suite for Nuclear Medicine

An end-to-end environment for developing and interrogating deep learning models on nuclear medicine and radiological images. It handles study import,…

XAI Suite and Evidence-based AI validation tools

A cross-domain workbench for building, explaining and — critically — validating AI models before anyone trusts them. It couples model…

A Review on SPECT Myocardial Perfusion Imaging Attenuation Correction Using Deep Learning

Ioannis D. Apostolopoulos, Nikolaοs Ι. Papandrianos, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos

Applied Sciences — Vol. 15, No. 20, pp. 11287 10.3390/app152011287

Clinical validation of the EMERALD’s MDSS t the University Hospital of Patras

On April 1st, 2025, the developed Medical Decision Support System (MDSS) was clinically validated at the University Hospital of Patras,…

Fuzzy Cognitive Explainable Analytics for Translating Model Complexity in Nuclear Medical Diagnosis (EMERALD)

EMERALD takes a unique, holistic approach to patient-specific predictive modeling and MDSS development by extracting and integrating knowledge from new…

Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis

Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Dimitrios J. Apostolopoulos and Elpiniki Papageorgiou

Bioengineering — 11(10), 957 10.3390/bioengineering11100957/s1

A Fuzzy Cognitive Map learning approach for coronary artery disease diagnosis in Nuclear Medicine

Anna Feleki, Ioannis D. Apostolopoulos, Konstantinos Papageorgiou, Elpiniki I Papageorgiou, Dimitris J Apostolopoulos, Nikolaos I Papandrianos

13th Conference of the European Society for Fuzzy Logic and Technology 10.1007/978-3-031-39965-7_2

AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review

Nikolaos I. Papandrianos, Ioannis D. Apostolopoulos, Anna Feleki, Serafeim Moustakidis, Konstantinos Kokkinos, Elpiniki I. Papageorgiou

Nuclear Medicine Communications — Vol. 44, No. 1, pp. 1-11 10.1097/mnm.0000000000001634

Classification models for assessing coronary artery disease instances using clinical and biometric data: an explainable man-in-the-loop approach

Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, Nikolaos Papandrianos, Elpiniki Papageorgiou

Scientific Reports — Vol. 13, No. 1 10.1038/s41598-023-33500-9

Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies

Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Anna Feleki, Serafeim Moustakidis, Elpiniki I. Papageorgiou

EJNMMI Physics — Vol. 10, No. 1 10.1186/s40658-022-00522-7

Diagnosis of Coronary Artery Disease from Myocardial Perfusion Imaging Polar Maps with an innovative attention-based feature-fusion network

Anna Feleki et al.

19th International Conference on Machine Learning and Data Mining MLDM

Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism

Dimitris J. Apostolopoulos, Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Trifon Spyridonidis, George S. Panayiotakis

Algorithms — Vol. 16, No. 9, pp. 435 10.3390/a16090435

Explainable Deep Fuzzy Cognitive Map Diagnosis of Coronary Artery Disease: Integrating Myocardial Perfusion Imaging, Clinical Data, and Natural Language Insights

Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Nikolaos Papathanasiou, Dimitrios Apostolopoulos, Nikolaos Papandrianos

Applied Sciences — Vol. 13, No. 21, pp. 11953 10.3390/app132111953

Innovative Attention-Based Explainable Feature-Fusion VGG19 Network for Characterising Myocardial Perfusion Imaging SPECT Polar Maps in Patients with Suspected Coronary Artery Disease

Ioannis D. Apostolopoulos, Nikolaοs D. Papathanasiou, Nikolaos Papandrianos, Elpiniki Papageorgiou, Dimitris J. Apostolopoulos

Applied Sciences — Vol. 13, No. 15, pp. 8839 10.3390/app13158839

Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models

Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Nikolaos Papandrianos

Applied Sciences — Vol. 13, No. 14, pp. 8120 10.3390/app13148120

A Deep Learning Methodology for the Detection of Abnormal Parathyroid Glands via Scintigraphy with 99mTc-Sestamibi

Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos

Diseases — Vol. 10, No. 3, pp. 56 10.3390/diseases10030056

An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM

Nikolaos I. Papandrianos, Anna Feleki, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Ioannis D. Apostolopoulos, Dimitris J. Apostolopoulos

Applied Sciences — Vol. 12, No. 15, pp. 7592 10.3390/app12157592

Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review

Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos, George S. Panayiotakis

European Journal of Nuclear Medicine and Molecular Imaging — Vol. 49, No. 11, pp. 3717-3739 10.1007/s00259-022-05805-w

Artificial Intelligence Methods for Identifying and Localizing Abnormal Parathyroid Glands: A Review Study

Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos

Machine Learning and Knowledge Extraction — Vol. 4, No. 4, pp. 814-826 10.3390/make4040040

Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease

Nikolaos I. Papandrianos, Ioannis D. Apostolopoulos, Anna Feleki, Dimitris J. Apostolopoulos, Elpiniki I. Papageorgiou

Annals of Nuclear Medicine — Vol. 36, No. 9, pp. 823-833 10.1007/s12149-022-01762-4

Detection and Localisation of Abnormal Parathyroid Glands: An Explainable Deep Learning Approach

Dimitris J. Apostolopoulos, Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Trifon Spyridonidis, George S. Panayiotakis

Algorithms — Vol. 15, No. 12, pp. 455 10.3390/a15120455

Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic

Ioannis D. Apostolopoulos, Besiana A Tzani

IISA 2022 10.1109/IISA56318.2022.9904388

Advanced fuzzy cognitive maps: state-space and rule-based methodology for coronary artery disease detection

Ioannis D Apostolopoulos, Peter P Groumpos, Dimitris J Apostolopoulos

Biomedical Physics & Engineering Express — Vol. 7, No. 4, pp. 045007 10.1088/2057-1976/abfd83

CORONARY ARTERY DISEASE DIAGNOSIS USING MYOCARDIAL PERFUSION IMAGING POLAR MAPS AND DEEP LEARNING METHODS

15th Panhellenic Conference of Nuclear Medicine — May 27-30, 2021, Online 10.13140/RG.2.2.27879.57768

Multi-Input Deep Learning Approach for Cardiovascular Disease Diagnosis using Myocardial Perfusion Imaging and Clinical Data

Ioannis D. Apostolopoulos, Dimitris I. Apostolopoulos, Trifon I. Spyridonidis, Nikolaos D. Papathanasiou, George S. Panayiotakis

Physica Medica 10.1016/j.ejmp.2021.04.011

Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation

Ioannis D. Apostolopoulos, Nikolaos D Papathanasiou, Trifon Spyridonidis, Dimitris J Apostolopoulos

Hellenic Journal of Nuclear Medicine 10.1967/s002449912101

Non – invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps

Ioannis D. Apostolopoulos, Peter P. Groumpos

Computer Methods in Biomechanics and Biomedical Engineering — Vol. 23, No. 12, pp. 879-887 10.1080/10255842.2020.1768534

A DECISION MAKING SUPPORT SYSTEM IN NUCLEAR MEDICINE USING FUZZY COGNITIVE MAPS

Apostolopoulos I.D. et al.

7o ΠΑΝΕΛΛΗΝΙΟ ΣΥΝΕΔΡΙΟ ΒΙΟΪΑΤΡΙΚΗΣ ΤΕΧΝΟΛΟΓΙΑΣ — April 7, 2017, Athens, Greece 10.13140/RG.2.2.26912.94724

A Medical Decision Support System for the Prediction of the Coronary Artery Disease Using Fuzzy Cognitive Maps

Ioannis D. Apostolopoulos, Peter P Groumpos, Dimitris I Apostolopoulos

Creativity in Intelligent Technologies and Data Science 10.1007/978-3-319-65551-2_20

Diagnostics

Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou and George S. Panayiotakis

Diagnostics 10.3390/diagnostics