Nonrigid registration of medical image based on adaptive local structure tensor and normalized mutual information
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.12612
Abstract: Abstract Nonrigid registration of medical images is especially critical in clinical treatment. Mutual information is a popular similarity measure for medical image registration; however, only the intensity statistical characteristics of the global consistency of image… read more here.
Keywords: information; mutual information; registration; medical image ... See more keywords
Reinforcement learning in medical image analysis: Concepts, applications, challenges, and future directions
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DOI: 10.1002/acm2.13898
Abstract: Abstract Motivation Medical image analysis involves a series of tasks used to assist physicians in qualitative and quantitative analyses of lesions or anatomical structures which can significantly improve the accuracy and reliability of medical diagnoses… read more here.
Keywords: reinforcement learning; medical image; learning medical; analysis ... See more keywords
A porosity model for medical image segmentation of vessels
Sign Up to like & getrecommendations! Published in 2022 at "International Journal for Numerical Methods in Biomedical Engineering"
DOI: 10.1002/cnm.3580
Abstract: A physics‐based medical image segmentation method is developed. Specifically, the image greyscale intensity is used to infer the voxel partial volumes and subsequently formulate a porous medium analogy. The method involves first translating the medical… read more here.
Keywords: image segmentation; medical image; segmentation; method ... See more keywords
IGM‐based perceptual multimodal medical image fusion using free energy motivated adaptive PCNN
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22261
Abstract: Multimodal medical image fusion merges two medical images to produce a visual enhanced fused image, to provide more accurate comprehensive pathological information to doctors for better diagnosis and treatment. In this article, we present a… read more here.
Keywords: multimodal medical; image; fusion; medical image ... See more keywords
Improving medical image fusion method using fuzzy entropy and nonsubsampling contourlet transform
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22476
Abstract: Many types of medical images must be fused, as single‐modality medical images can only provide limited information due to the imaging principles and the complexity of human organ structures. In this paper, a multimodal medical… read more here.
Keywords: image; fuzzy entropy; method; fusion ... See more keywords
Medical image fusion based on local Laplacian decomposition and iterative joint filter
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22714
Abstract: Previous multi‐modal medical image fusion methods have suffered from color distortion, blurring, and noise. To address these problems, we propose a method for integrating the information contained in functional and anatomical medical images. In the… read more here.
Keywords: iterative joint; medical image; local laplacian; image fusion ... See more keywords
Modified U‐Net for cytological medical image segmentation
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22732
Abstract: Deep learning–based medical image segmentation is henceforth widely established as a powerful segmentation process. This article proposes a new U‐Net architecture based on a convolutional neural network for cytology image segmentation. This structure is more… read more here.
Keywords: image segmentation; medical image; segmentation; cytological medical ... See more keywords
A novel adaptive cubic quasi‐Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID‐19 and segmentation for COVID‐19 lung infection, liver tumor, and optic disc/cup
Sign Up to like & getrecommendations! Published in 2022 at "Medical Physics"
DOI: 10.1002/mp.15969
Abstract: Abstract Background Most of existing deep learning research in medical image analysis is focused on networks with stronger performance. These networks have achieved success, while their architectures are complex and even contain massive parameters ranging… read more here.
Keywords: covid; detection covid; segmentation; image analysis ... See more keywords
An efficient interactive segmentation framework for medical images without pre-training.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16120
Abstract: BACKGROUND AND PURPOSE Accurate and efficient medical image segmentation plays an important role in subsequent clinical applications such as diagnosis and surgical planning. This paper proposes an efficient interactive framework based on a graph convolutional… read more here.
Keywords: efficient interactive; framework; medical image; segmentation ... See more keywords
Semi-supervised medical image segmentation via cross-guidance and feature-level consistency dual regularization schemes.
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DOI: 10.1002/mp.16217
Abstract: BACKGROUND Semi-supervised learning is becoming an effective solution for medical image segmentation because of the lack of a large amount of labeled data. PURPOSE Consistency-based strategy is widely used in semi-supervised learning. However, it is still… read more here.
Keywords: semi supervised; image segmentation; regularization; medical image ... See more keywords
FaxMatch: Multi-Curriculum Pseudo-Labeling for Semi-supervised Medical Image Classification.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16312
Abstract: BACKGROUND Semi-supervised learning (SSL) can effectively use information from unlabeled data to improve model performance, which has great significance in medical imaging tasks. Pseudo-labeling is a classical SSL method that uses a model to predict… read more here.
Keywords: semi supervised; pseudo labeling; medical image; pseudo ... See more keywords