Results 51 to 60 of about 914,658 (364)
BMC Medical Imaging, 2021 Background The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. Still, current image segmentation platforms do not provide the required functionalities for plain setup of medical ...
Dominik Müller, Frank Kramer
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Regmentation: A New View of Image Segmentation and Registration [PDF]
, 2012 Image segmentation and registration have been the two major areas of research in the medical imaging community for decades and still are. In the context of radiation oncology, segmentation and registration methods are widely used for target structure ...
Erdt, Marius +2 more
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A Parallel Fuzzy C-Mean algorithm for Image Segmentation [PDF]
, 2004 This paper proposes a parallel Fuzzy C-Mean (FCM) algorithm for image segmentation. The sequential FCM algorithm is computationally intensive and has significant memory requirements.
Chhillar, D. +3 more
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STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training [PDF]
arXiv.org, 2023 Large-scale models pre-trained on large-scale datasets have profoundly advanced the development of deep learning. However, the state-of-the-art models for medical image segmentation are still small-scale, with their parameters only in the tens of ...
Ziyan Huang +10 more
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EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation [PDF]
Computer Vision and Pattern RecognitionAn efficient and effective decoding mechanism is crucial in medical image segmentation, especially in scenarios with limited computational resources. However, these decoding mechanisms usually come with high computational costs.
Md Mostafijur Rahman +2 more
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DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling
NeuroImageThis study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computational ...
Zongren Li +3 more
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A Latent Source Model for Patch-Based Image Segmentation
, 2015 Despite the popularity and empirical success of patch-based nearest-neighbor and weighted majority voting approaches to medical image segmentation, there has been no theoretical development on when, why, and how well these nonparametric methods work.
Chen, George +2 more
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, 2018 Uncertainty estimation methods are expected to improve the understanding and quality of computer-assisted methods used in medical applications (e.g., neurosurgical interventions, radiotherapy planning), where automated medical image segmentation is ...
Blatti-Moreno, Marcela +6 more
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Pixel Diffuser: Practical Interactive Medical Image Segmentation without Ground Truth
Bioengineering, 2023 Medical image segmentation is essential for doctors to diagnose diseases and manage patient status. While deep learning has demonstrated potential in addressing segmentation challenges within the medical domain, obtaining a substantial amount of data ...
Mingeon Ju +5 more
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Current Directions in Biomedical Engineering, 2017 Multimodal imaging is gaining in importance in the field of personalized medicine and can be described as a current trend in medical imaging diagnostics. The segmentation, classification and analysis of tissue structures is essential.
Stich Manuel +3 more
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