[HTML][HTML] Closing the translation gap: AI applications in digital pathology
Recent advances in artificial intelligence show tremendous promise to improve the
accuracy, reproducibility, and availability of medical diagnostics across a number of medical …
accuracy, reproducibility, and availability of medical diagnostics across a number of medical …
A review on biomedical image processing and future trends
AP Dhawan - Computer Methods and Programs in Biomedicine, 1990 - Elsevier
The last two decades have witnessed a revolutionary development in the field of biomedical
and diagnostic imaging. Imaging procedures and modalities which were only in the …
and diagnostic imaging. Imaging procedures and modalities which were only in the …
Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction
Background There is growing interest in utilizing artificial intelligence, and particularly deep
learning, for computer vision in histopathology. While accumulating studies highlight expert …
learning, for computer vision in histopathology. While accumulating studies highlight expert …
Histopathological images analysis and predictive modeling implemented in digital pathology—current affairs and perspectives
In modern clinical practice, digital pathology has an essential role, being a technological
necessity for the activity in the pathological anatomy laboratories. The development of …
necessity for the activity in the pathological anatomy laboratories. The development of …
Digital pathology: Data-intensive frontier in medical imaging
Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic
examination of tissue reveals information enabling the pathologist to render accurate …
examination of tissue reveals information enabling the pathologist to render accurate …
Artificial neural networks and pathologists recognize basal cell carcinomas based on different histological patterns
S Kimeswenger, P Tschandl, P Noack… - Modern …, 2021 - nature.com
Recent advances in artificial intelligence, particularly in the field of deep learning, have
enabled researchers to create compelling algorithms for medical image analysis …
enabled researchers to create compelling algorithms for medical image analysis …
Intelligent feature engineering and ontological mapping of brain tumour histomorphologies by deep learning
K Faust, S Bala, R Van Ommeren, A Portante… - Nature Machine …, 2019 - nature.com
Deep learning is an emerging transformative tool in diagnostic medicine, yet limited access
and the interpretability of learned parameters hinders widespread adoption. Here we have …
and the interpretability of learned parameters hinders widespread adoption. Here we have …
Pathology imaging informatics for quantitative analysis of whole-slide images
Objectives With the objective of bringing clinical decision support systems to reality, this
article reviews histopathological whole-slide imaging informatics methods, associated …
article reviews histopathological whole-slide imaging informatics methods, associated …
CognitionMaster: an object-based image analysis framework
S Wienert, D Heim, M Kotani, B Lindequist… - Diagnostic …, 2013 - Springer
Background Automated image analysis methods are becoming more and more important to
extract and quantify image features in microscopy-based biomedical studies and several …
extract and quantify image features in microscopy-based biomedical studies and several …
Artificial intelligence and digital pathology: clinical promise and deployment considerations
MD Zarella, DS McClintock, H Batra… - Journal of Medical …, 2023 - spiedigitallibrary.org
Artificial intelligence (AI) presents an opportunity in anatomic pathology to provide
quantitative objective support to a traditionally subjective discipline, thereby enhancing …
quantitative objective support to a traditionally subjective discipline, thereby enhancing …