[HTML][HTML] Transparency of deep neural networks for medical image analysis: A review of interpretability methods
Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
A review on deep-learning algorithms for fetal ultrasound-image analysis
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …
fetal images. A number of survey papers in the field is today available, but most of them are …
FUTURE-AI: guiding principles and consensus recommendations for trustworthy artificial intelligence in medical imaging
The recent advancements in artificial intelligence (AI) combined with the extensive amount
of data generated by today's clinical systems, has led to the development of imaging AI …
of data generated by today's clinical systems, has led to the development of imaging AI …
Towards clinical application of artificial intelligence in ultrasound imaging
Artificial intelligence (AI) is being increasingly adopted in medical research and applications.
Medical AI devices have continuously been approved by the Food and Drug Administration …
Medical AI devices have continuously been approved by the Food and Drug Administration …
Attention-based saliency maps improve interpretability of pneumothorax classification
Purpose To investigate the chest radiograph classification performance of vision
transformers (ViTs) and interpretability of attention-based saliency maps, using the example …
transformers (ViTs) and interpretability of attention-based saliency maps, using the example …
Explainable AI for Medical Data: Current Methods, Limitations, and Future Directions
With the power of parallel processing, large datasets, and fast computational resources,
deep neural networks (DNNs) have outperformed highly trained and experienced human …
deep neural networks (DNNs) have outperformed highly trained and experienced human …
Segmentation-based vs. regression-based biomarker estimation: a case study of fetus head circumference assessment from ultrasound images
The fetus head circumference (HC) is a key biometric to monitor fetus growth during
pregnancy, which is estimated from ultrasound (US) images. The standard approach to …
pregnancy, which is estimated from ultrasound (US) images. The standard approach to …
On the evaluation of deep learning interpretability methods for medical images under the scope of faithfulness
V Lamprou, A Kallipolitis, I Maglogiannis - Computer Methods and …, 2024 - Elsevier
Abstract Background and Objective: Evaluating the interpretability of Deep Learning models
is crucial for building trust and gaining insights into their decision-making processes. In this …
is crucial for building trust and gaining insights into their decision-making processes. In this …
Construction of an end‐to‐end regression neural network for the determination of a quantitative index sagittal root inclination
Y Lin, M Shi, D Xiang, P Zeng, Z Gong… - Journal of …, 2022 - Wiley Online Library
Background Immediate implant placement in the esthetic area requires comprehensive
assessments with nearly 30 quantitative indexes. Most artificial intelligence (AI)‐driven …
assessments with nearly 30 quantitative indexes. Most artificial intelligence (AI)‐driven …
Deep Learning Techniques for Foetal and Infant Data Processing in a Medical Context
In recent years, deep learning algorithms have become the standard approach for analyzing
fetal images obtained through ultrasound technology. This chapter surveys the most up-to …
fetal images obtained through ultrasound technology. This chapter surveys the most up-to …