CORTEXA
← Browse
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26Cited by 0

Tissue-Mimicking Phantoms: From Imitating Human Tissue to Measurement Reliability: A Review of the Metrological Evaluation of Tissue-Mimicking Phantoms in Acoustic, Optical, and Photoacoustic Imaging

Hüseyin Okan Durmuş

This review examines tissue-mimicking phantoms from a metrological perspective, emphasizing that their scientific value lies not in reproducing biological tissue itself, but in providing reliable, traceable, and uncertainty-characterized measurements for medical imaging systems. The paper reviews the current literature on acoustic, optical, and photoacoustic tissue-mimicking phantoms, discussing the physical properties required for different imaging modalities, fabrication methods, characterization techniques, measurement uncertainty, long-term stability, digital twin approaches, artificial intelligence, and population diversity. A conceptual metrological framework is proposed, highlighting that phantom development should extend beyond material fabrication to include characterization, uncertainty evaluation, traceability, inter-laboratory comparison, and reference value assignment. The review argues that the future of phantom research will increasingly depend on measurement reliability rather than on material realism alone. Keywords: tissue-mimicking phantom, metrology, ultrasound imaging, photoacoustic imaging, optical imaging, measurement uncertainty, traceability, digital twin, medical imaging.

View free PDFSource page

Related papers

openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

Dataset for "Deep learning models for estimating volume and Lorey's height across Nordic countries using optical and SAR satellite images" article

Zsófia Koma, Oleg Antropov, Jukka Miettinen, Johannes Breidenbach

This repository contains the data products and code required to reproduce the results presented in the article "Deep Learning Models for Estimating Volume and Lorey's Height Across Nordic Countries Using Optical and SAR Satellite Images". The study investigates the use of U-Net d…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Cognitive Cyborgification: A Bloom-Based Framework for Measuring the Externalization of Human Cognition to AI

K. Yamada

The externalization of cognitive abilities to tools is not new. Writing externalized memory; calculators externalized computation; search engines externalized knowledge retrieval. Each generation lost the skills its predecessors possessed, naturalized its tools, and claimed autho…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-15

Deep Learning for Human Activity Recognition: A Comprehensive Review of Architectures, Performance, and Challenges Across Five Sensory Datasets

Abeer FathAllah Brery, Ascensión Gallardo-Antolín, Mahmoud Fakhry, Israel Gonzalez-Carrasco

Human activity recognition (HAR) using sensor data allows the automatic detection of human behavior and actions in everyday environments. The development of scalable and privacy-preserving HAR systems is supported by the nonintrusive collection of time-series data using wearable…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Show Your Work: From Disclosing AI Use to Demonstrating Rigour. A Worked Case and a Contributor-Role Standard for AI-Assisted Scholarship

Johan Locke

Background. Publishing has settled on one answer to generative AI: an AI cannot be an author, and its use must be disclosed. Problem. Disclosure asks the wrong question. A statement that AI was used cannot be falsified in either direction, and a large recent study suggests it is…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

Kenya Forest Sounds Dataset

Allan Vikiru, Daniel Simiyu, Sandra Kahoro, Zainabu Muti, Solomon Kamau, Anthony Macharia, et al.

Kenya Forest Sounds Dataset License: Creative Commons Attribution 4.0 International (CC BY 4.0) Authors and Contributors All authors and contributors are listed on Zenodo: https://zenodo.org/records/21443074 About The Kenya Forest Sounds Dataset contains 5,500 audio recordings co…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Comparative Analysis of Machine Learning Classification Algorithms and Hybrid Models for Student Performance Prediction

Ms. Pooja C. Soni, Dr. Hetal R. Modi, PC Negi

This study focuses on the analysis and comparison of machine learning classification algorithms and hybrid machine learning models for predicting student academic performance. Educational Data Mining techniques are used to extract meaningful insights from student datasets. Variou…

View free PDFSource page