SIPPRE

Assistant Professor @ECE UoP

Special Issue Call for Papers: Explainable AI in Medical Imaging

/ / Lab News

The SIPPRE Research Group is pleased to announce a Special Issue on “Explainable AI in Medical Imaging: Toward Transparent and Trustworthy Diagnostic Systems” in the journal Applied Sciences (ISSN 2076-3417).

About the Special Issue

Artificial intelligence (AI) offers tremendous potential for improving medical imaging diagnostics. However, the “black box” nature of many AI models—particularly deep learning systems—presents significant challenges for clinical adoption. This Special Issue focuses on the rapidly evolving field of explainable AI (xAI), which aims to enhance transparency, interpretability, and trust in automated diagnostic systems.

Topics of Interest

We welcome submissions on various aspects of explainable AI in medical imaging, including but not limited to:

  • Novel methods and frameworks for interpretable AI in medical imaging
  • Theoretical foundations of explainable AI for medical applications
  • Algorithmic developments that enhance model transparency
  • Evaluation strategies for explainable medical imaging systems
  • Clinical validations of xAI techniques
  • Approaches balancing high performance with meaningful insights for clinicians

Guest Editors

  • Dr. Athanasios Koutras – University of the Peloponnese, Greece
  • Dr. Dermatas Evangelos – University of Patras, Greece
  • Dr. Ioanna Christoyianni – University of Patras, Greece
  • Dr. George Apostolopoulos – University of Patras, Greece

Important Information

  • Submission Deadline: November 20, 2025
  • Journal Section: Biomedical Engineering
  • Submission Types: Research articles, review articles, and short communications

How to Submit

Manuscripts should be submitted through the MDPI submission system. Please visit the Special Issue website for detailed submission instructions.

All submissions will undergo a rigorous peer-review process. Accepted papers will be published continuously in the journal and listed together on the Special Issue website.

Contact

For questions related to this Special Issue, please contact any of the Guest Editors or the SIPPRE Research Group.

Applied Sciences is an international, peer-reviewed, open-access journal published by MDPI. The journal has a CiteScore of 3.7 (2023) and is indexed in the Science Citation Index Expanded (Web of Science), Scopus, and other databases.

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Research Participants Needed: Music & Brain Activity Study

/ / Brain Computer Interface, Experiments, Lab News

The SIPPRE Group at the ECE Department, is seeking volunteers to participate in our innovative NeuroRock EEG study.

The Experience
  • Listen to carefully selected instrumental rock music through high-quality headphones
  • Wear Enophones, a comfortable and non-invasive EEG headset that feels similar to regular headphones
  • Share your emotional responses to different music styles
  • Total time commitment: Approximately 60 minutes
What to Expect

During this relaxing session, you’ll listen to various rock music selections while we record your brain’s natural responses. The Enophones provide a comfortable recording experience with minimal setup—no gels or extensive preparation required.

This research supports our groundbreaking NeuroRock Hackathon where EUNICE students will analyze how the brain processes emotional aspects of music.

How to Participate

Please contact Associate Professor Athanasios Koutras (koutras [AT] uop.gr) for scheduling or additional information.

All data will be anonymized and handled according to research ethics guidelines.

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Announcing: NeuroRock Hackathon 2025!

/ / Brain Computer Interface, Lab News
Decode the Brain’s Response to Music

The SIPPRE Group is thrilled to announce our first-ever NeuroRock Hackathon, exclusively for EUNICE students enrolled in the “Decoding Life Signals: Innovations in Biomedical Engineering” course.

The Challenge

Teams will analyze EEG data recorded while participants experience emotional rock music. Your mission: develop algorithms to decode emotional states from brain activity and predict subjective experiences.

Key Information
  • Deadline: June 5, 2025
  • Format: Work in pairs to develop Python-based analysis
  • Experience Required: None! We provide starter code and guidance

This is your chance to apply classroom knowledge to real neuroscience data and explore the fascinating intersection of music, emotions, and brain activity.

Ready to Rock Your Brain?

Keep an eye on your course announcements for complete details, or contact Prof. Athanasios Koutras with questions.

For EUNICE students only. No prior EEG experience necessary.

Announcing: NeuroRock Hackathon 2025! Read More »

COURSE LAUNCH: Decoding Life Signals: Innivations on Biomedical Engineering 2025 Begins!

/ / Courses

The Signal, Image Processing and Pattern Recognition Research Group (SIPPRE) is excited to announce the commencement of our EUNICE course “Decoding Life Signals: Innovations in Biomedical Engineering.”

We’re thrilled to welcome 23 talented students from Italy, Portugal, Germany, Ukraine, Poland, Spain and Greece to this innovative program. The international diversity of our cohort promises to bring unique perspectives and collaborative opportunities to our biomedical signal processing journey.

Starting this February, our students will:
– Master real-time biosignal acquisition and analysis
– Develop brain-computer interfaces
– Apply machine learning in healthcare
– Collaborate on international projects

First Lecture: 17/2/2025
Follow our progress and student achievements throughout the semester!

COURSE LAUNCH: Decoding Life Signals: Innivations on Biomedical Engineering 2025 Begins! Read More »

Special Issue on Audio, Speech and Music Processing and Analysis

/ / Lab News

We are excited to announce that members of the SIPPRE Research Group are serving as Guest Editors for a special issue of the journal Electronics, titled:

“Recent Advances in Audio, Speech, and Music Processing and Analysis”

This special issue aims to highlight state-of-the-art research in audio, speech, and music processing, focusing on emerging applications, algorithms, and systems. Topics of interest include:

  • Speech recognition, speaker verification, and voice synthesis.
  • Audio compression and noise cancelation.
  • Music information retrieval and recommendation systems.
  • Autonomous and semi-autonomous computer musicians.

Guest Editors:

  • Dr. Athanasios Koutras (University of the Peloponnese, Greece)
  • Dr. Chrisoula Alexandraki (Hellenic Mediterranean University, Greece)

Submission Details:

  • Deadline: January 15, 2025
  • Impact Factor: 2.6
  • CiteScore: 5.3

This is an excellent opportunity for researchers and practitioners to disseminate innovative work in the field of audio, speech, and music processing. Accepted manuscripts will be published open-access, ensuring global visibility and accessibility.

For more information and manuscript submissions, visit the Special Issue Page.

We look forward to your contributions to this exciting field of research!

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Announcement: Special Issue Guest Edited by SIPPRE Lab Members

/ / Lab News

We are delighted to announce that members of the SIPPRE Research Group are serving as Guest Editors for a special issue of the journal Applied Sciences, titled:

“Diagnosis of Medical Imaging”

This special issue focuses on the latest advancements in medical imaging, including novel techniques, machine-learning approaches, and innovative diagnostic tools that push the boundaries of healthcare technology.

Guest Editors:

Dr. Athanasios Koutras, Dr. Evangelos Dermatas, Dr. Ioanna Christoyianni, Dr. George Apostolopoulos

Submission Details:

  • Deadline: April 20, 2025
  • Impact Factor: 2.5
  • CiteScore: 5.3

We invite researchers, practitioners, and industry professionals to contribute their work and share insights into this exciting field. Accepted papers will be published in an open-access format, ensuring maximum visibility and accessibility.

For more information and to submit your manuscript, visit the Special Issue Page.

We look forward to receiving your contributions and advancing the field of medical imaging together!

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New Publication by PhD Student Dionysios Anyfantis

/ / Publications

We are proud to announce the latest publication from our lab in the prestigious journal Electronics:

“Revealing Occult Malignancies in Mammograms Through GAN-Driven Breast Density Transformation”

Authored by Dionysios Anyfantis, PhD student at the SIPPRE Lab, in collaboration with our team, this work explores the application of CycleGANs to transform mammograms of dense breast tissue into lower-density representations. By doing so, the study significantly improves the detection of hidden abnormalities, contributing to the advancement of breast cancer diagnostics.

This innovative research highlights the intersection of deep learning and medical imaging, showcasing how AI can revolutionize healthcare and assist radiologists in making more accurate diagnoses.

You can access the full paper here.

Congratulations to Dionysios Anyfantis for this outstanding achievement and his continued contributions to medical imaging and AI research. We look forward to seeing more groundbreaking work from him in the future!

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New Course – Decoding Life Signals: Innovations in Biomedical Engineering

/ / Courses

We are excited to announce a new course, “Decoding Life Signals: Innovations in Biomedical Engineering,” offered by Prof. Athanasios Koutras, Dr. Nyi Nyi Tun, and Dionysios Anyfantis, through the EUNICE European University Alliance.

About EUNICE

EUNICE (European University for Customized Education) is a prestigious alliance of nine universities across Europe, designed to foster innovation, interdisciplinary learning, and international collaboration. EUNICE aims to create a unified academic environment, offering students diverse opportunities to engage in cutting-edge courses, such as this one, that address global challenges and drive impactful research.

Course Highlights

This interdisciplinary course explores the fascinating world of biomedical signals (EEG, ECG, EMG) and provides a blend of theoretical and practical knowledge:

  • Data Analysis and Machine Learning: Process, analyze, and visualize biomedical data using tools like Python and MNE-Python.
  • Real-World Applications: Investigate applications in healthcare, such as Brain-Computer Interfaces (BCIs) and neural signal processing.
  • Project-Based Learning: Develop hands-on experience through projects tackling real-world biomedical challenges.
  • Expert Guidance: Learn from distinguished faculty and guest lecturers, bringing expertise from both academia and industry.

Course Details

  • Language of Instruction: English
  • Delivery Mode: Online, live sessions with practical exercises and collaborative projects.
  • Duration: February to May 2025 (12 weeks)
  • Eligibility: Open to Bachelor’s and Master’s students across EUNICE partner universities, with interest or background in Python programming and biomedical signal processing.

Additional Features

  • Live Demonstrations: Practical sessions with OpenBCI and EmotiBit, showcasing EEG and physiological signal acquisition techniques.
  • International Collaboration: Work in teams with students from various EUNICE universities, fostering global connections and interdisciplinary learning.
  • Resources: Access all course materials, including lecture notes, projects, and tools, through the SIPPRE Lab’s repository and GitHub page.

Join us in this unique opportunity to explore the cutting-edge intersection of technology and healthcare while benefiting from EUNICE’s commitment to international collaboration and quality education.

For enrollment details, visit the EUNICE website at EUNICE Courses or contact Prof. Athanasios Koutras at koutras@uop.gr.

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New Addition to the SIPPRE Lab: Tello RoboMaster TT Drone

/ / Equipment

We are excited to announce the latest addition to the SIPPRE Lab’s equipment: the Tello RoboMaster TT drone! This programmable drone, compatible with Python, opens up exciting possibilities for innovative research and student projects.

The RoboMaster TT will be a centerpiece in various projects, including:

  • Brain-Computer Interface (BCI) Applications: Controlling the drone using brain and muscle signals to explore advanced human-machine interaction techniques.
  • Computer Vision Programs: Implementing face detection, face recognition, and person tracking to enhance autonomous navigation capabilities.
  • Swarm Intelligence Studies: Investigating collaborative drone behaviors and multi-agent systems, which have applications in search and rescue or environmental monitoring.
  • Gesture-Based Control: Designing systems where gestures captured by cameras or motion sensors control the drone’s movements.
  • Augmented Reality Integration: Combining drone operation with augmented reality for immersive experiences in education or entertainment.

This versatile drone will also serve as a cornerstone for final diploma thesis projects, providing students with hands-on experience in signal processing, machine learning, robotics, and more.

Stay tuned for updates as we explore the limitless potential of this powerful tool in research and education!

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Welcoming Dr. Nyi Nyi Tun to the SIPPRE Lab

/ / Positions

We are delighted to welcome Dr. Nyinyi Tun to the SIPPRE Lab as a postdoctoral researcher! Dr. Tun joins us from Kyushu University, where he made significant contributions to biomedical engineering and brain-computer interface (BCI) research.

At the SIPPRE Lab, Dr. Tun will work alongside Prof. Athanasios Koutras on an exciting project focusing on Silent Speech BCI. This cutting-edge research aims to develop novel EEG modalities to decode speech intentions directly from brain activity, pushing the boundaries of non-invasive communication technologies.

Dr. Tun brings a wealth of expertise and a passion for innovation to this collaboration, and we are thrilled to have him as part of our team.

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