[HTML][HTML] Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with
respect to the quantity of high-performing solutions reported in the literature. End users are …
respect to the quantity of high-performing solutions reported in the literature. End users are …
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
The comprehensive integration of machine learning healthcare models within clinical
practice remains suboptimal, notwithstanding the proliferation of high-performing solutions …
practice remains suboptimal, notwithstanding the proliferation of high-performing solutions …
Etiology of white matter hyperintensities in autosomal dominant and sporadic Alzheimer disease
Z Shirzadi, SA Schultz, WYW Yau… - JAMA …, 2023 - jamanetwork.com
Importance Increased white matter hyperintensity (WMH) volume is a common magnetic
resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) …
resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) …
Improved Dementia Prediction in Cerebral Small Vessel Disease Using Deep Learning–Derived Diffusion Scalar Maps From T1
BACKGROUND: Cerebral small vessel disease is the most common pathology underlying
vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to …
vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to …
Vascular burden and cognition: mediating roles of neurodegeneration and amyloid PET
It remains unclear to what extent cerebrovascular burden relates to amyloid beta (Aβ)
deposition, neurodegeneration, and cognitive dysfunction in mixed disease populations with …
deposition, neurodegeneration, and cognitive dysfunction in mixed disease populations with …
Deep learning in neuroimaging data analysis: applications, challenges, and solutions
LK Avberšek, G Repovš - Frontiers in neuroimaging, 2022 - frontiersin.org
Methods for the analysis of neuroimaging data have advanced significantly since the
beginning of neuroscience as a scientific discipline. Today, sophisticated statistical …
beginning of neuroscience as a scientific discipline. Today, sophisticated statistical …
Progressive white matter injury in preclinical dutch cerebral amyloid angiopathy
Autosomal‐dominant, Dutch‐type cerebral amyloid angiopathy (D‐CAA) offers a unique
opportunity to develop biomarkers for pre‐symptomatic cerebral amyloid angiopathy (CAA) …
opportunity to develop biomarkers for pre‐symptomatic cerebral amyloid angiopathy (CAA) …
[HTML][HTML] ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI
Deep artificial neural networks (DNNs) have moved to the forefront of medical image
analysis due to their success in classification, segmentation, and detection challenges. A …
analysis due to their success in classification, segmentation, and detection challenges. A …
Stochastic uncertainty quantification techniques fail to account for inter-analyst variability in white matter hyperintensity segmentation
B Philps, M del C. Valdes Hernandez… - Annual Conference on …, 2024 - Springer
Abstract White Matter Hyperintensities (WMH) are important neuroradiological markers of
small vessel disease in brain MRI, with automatic segmentation tasks essential in research …
small vessel disease in brain MRI, with automatic segmentation tasks essential in research …
Deep learning applications in vascular dementia using neuroimaging
C Dong, S Hayashi - Current Opinion in Psychiatry, 2024 - journals.lww.com
Deep learning neural networks with neuroimaging data in VaD research represent
significant promise for advancing early diagnosis and treatment strategies. Ongoing …
significant promise for advancing early diagnosis and treatment strategies. Ongoing …