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[HTML][HTML] A review of uncertainty estimation and its application in medical imaging
The use of AI systems in healthcare for the early screening of diseases is of great clinical
importance. Deep learning has shown great promise in medical imaging, but the reliability …
importance. Deep learning has shown great promise in medical imaging, but the reliability …
3D-printed multifunctional materials enabled by artificial-intelligence-assisted fabrication technologies
Z Zhu, DWH Ng, HS Park, MC McAlpine - Nature Reviews Materials, 2021 - nature.com
The emerging capability to 3D print a diverse palette of functional inks will enable the mass
democratization of patient-specific wearable devices and smart biomedical implants for …
democratization of patient-specific wearable devices and smart biomedical implants for …
Omnimedvqa: A new large-scale comprehensive evaluation benchmark for medical lvlm
Abstract Large Vision-Language Models (LVLMs) have demonstrated remarkable
capabilities in various multimodal tasks. However their potential in the medical domain …
capabilities in various multimodal tasks. However their potential in the medical domain …
Benchmark on automatic six-month-old infant brain segmentation algorithms: the iSeg-2017 challenge
L Wang, D Nie, G Li, É Puybareau… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Accurate segmentation of infant brain magnetic resonance (MR) images into white matter
(WM), gray matter (GM), and cerebrospinal fluid is an indispensable foundation for early …
(WM), gray matter (GM), and cerebrospinal fluid is an indispensable foundation for early …
Use of deep learning to predict final ischemic stroke lesions from initial magnetic resonance imaging
Importance Predicting infarct size and location is important for decision-making and
prognosis in patients with acute stroke. Objectives To determine whether a deep learning …
prognosis in patients with acute stroke. Objectives To determine whether a deep learning …
Sa-med2d-20m dataset: Segment anything in 2d medical imaging with 20 million masks
Segment Anything Model (SAM) has achieved impressive results for natural image
segmentation with input prompts such as points and bounding boxes. Its success largely …
segmentation with input prompts such as points and bounding boxes. Its success largely …