Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI | Paper Citation Record

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This paper cites an unresolved cited work.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Unresolved cited work

Reference 1

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This paper cites Usage of bias field correction might improve the predictability of tissue intensities.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Usage of bias field correction might improve the predictability of tissue intensities

Reference 2

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This paper cites Comparative analysis showed that the framework produces comparable BM -detection accuracy with the state-of -art approaches validated for significantly larger lesions.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Comparative analysis showed that the framework produces comparable BM -detection accuracy with the state-of -art approaches validated for significantly larger lesions

Reference 3

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This paper cites To our knowledge, no prior work focused on BM with volumes smaller than 500 mm 3.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI To our knowledge, no prior work focused on BM with volumes smaller than 500 mm 3

Reference 4

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This paper cites Computer-aided detection of metastatic brain tumors using magnetic resonance black-blood imaging,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Computer-aided detection of metastatic brain tumors using magnetic resonance black-blood imaging,

Reference 5

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This paper cites Please note that the input volume’s edge length is used in model naming, such as CropNet - mm, where is the volume’s edge length in mm.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Please note that the input volume’s edge length is used in model naming, such as CropNet - mm, where is the volume’s edge length in mm

Reference 6

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Observation 7a5b6e62-180b-4b3b-832c-ce18f2f0418b · outbound

This paper cites Epidemiology of brain metastases,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Epidemiology of brain metastases,

Reference 7

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This paper cites Computer-aided detection of brain metastases using a three -dimensional template-based matching algorithm,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Computer-aided detection of brain metastases using a three -dimensional template-based matching algorithm,

Reference 8

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This paper cites Computer-aided detection of metastatic brain tumors using automated three -dimensional template matching,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Computer-aided detection of metastatic brain tumors using automated three -dimensional template matching,

Reference 9

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This paper cites An approach for compute r-aided detection of brain metastases in post -Gd T1-W MRI,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI An approach for compute r-aided detection of brain metastases in post -Gd T1-W MRI,

Reference 10

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This paper cites Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network,

Reference 11

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This paper cites 3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI 3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models,

Reference 12

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This paper cites Automated robust image segmentation: Level set method using nonnegative matrix factorization with application to brain MRI,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Automated robust image segmentation: Level set method using nonnegative matrix factorization with application to brain MRI,

Reference 13

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This paper cites The system yielded an average Dice similarity coefficient of 0.67, where the detection false- positive rate in connection to the sensitivity percentage is not reported.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI The system yielded an average Dice similarity coefficient of 0.67, where the detection false- positive rate in connection to the sensitivity percentage is not reported

Reference 14

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This paper cites Computerized detection of metastatic brain tumors on contrast- enhanced 3D MR images by using a selective enhancement filter,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Computerized detection of metastatic brain tumors on contrast- enhanced 3D MR images by using a selective enhancement filter,

Reference 15

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This paper cites Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Reference 16

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This paper cites Detection and segmentation of brain metastases with deep convolutional networks,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Detection and segmentation of brain metastases with deep convolutional networks,

Reference 17

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This paper cites Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation,

Reference 18

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This paper cites A deep convolutional neural network -based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI A deep convolutional neural network -based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery,

Reference 19

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This paper cites The multimodal brain tumor image segmentation benchmark (BRATS),.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI The multimodal brain tumor image segmentation benchmark (BRATS),

Reference 20

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This paper cites Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI

Reference 21

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This paper cites Going deeper with convolutions,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Going deeper with convolutions,

Reference 22

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This paper cites Whole brain radiotherapy for brain metastasis,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Whole brain radiotherapy for brain metastasis,

Reference 23

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This paper cites Image matching using generalized scale -space interest points,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Image matching using generalized scale -space interest points,

Reference 24

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This paper cites Scale selection properties of generalized scale- space interest point detectors,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Scale selection properties of generalized scale- space interest point detectors,

Reference 25

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This paper cites 3D blob based brain tumor detection and segmentation in MR images,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI 3D blob based brain tumor detection and segmentation in MR images,

Reference 26

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This paper cites Machine learning and radiology,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Machine learning and radiology,

Reference 27

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This paper cites V -net: Fully convolutional neural networks for volumetric medical image segmentation,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI V -net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 28

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Observation f85c55d9-243c-47b3-b60f-9c4fe226ed86 · outbound

This paper cites Discriminative unsupervised feature learning with exemplar convolutional neural networks,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Discriminative unsupervised feature learning with exemplar convolutional neural networks,

Reference 29

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Observation 9d5e9f8a-823b-4954-83f1-55b3c0431fb6 · outbound

This paper cites U -net: Convolutional networks for biomedical image segmentation,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI U -net: Convolutional networks for biomedical image segmentation,

Reference 30

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This paper cites Best practices for convolutional neural networks appli ed to visual document analysis,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Best practices for convolutional neural networks appli ed to visual document analysis,

Reference 31

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This paper cites Tissue-based MRI intensity standardization: Application to multicentric datasets,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Tissue-based MRI intensity standardization: Application to multicentric datasets,

Reference 32

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This paper cites Evaluating intensity normalization on MRIs of human brain with multiple sclerosis,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Evaluating intensity normalization on MRIs of human brain with multiple sclerosis,

Reference 33

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This paper cites Normalization of brain magnetic resonance images using histogram even-order derivative analysis,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Normalization of brain magnetic resonance images using histogram even-order derivative analysis,

Reference 34

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This paper cites Comparison between intensity normalization techniques for dynamic susceptibility contrast (DSC) -MRI estimates of cerebral blood volume (CBV) in human gliomas,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Comparison between intensity normalization techniques for dynamic susceptibility contrast (DSC) -MRI estimates of cerebral blood volume (CBV) in human gliomas,

Reference 35

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This paper cites New variants of a method of MRI scale standardization,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI New variants of a method of MRI scale standardization,

Reference 36

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This paper cites Patch based intensity normalization of brain MR images,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Patch based intensity normalization of brain MR images,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:38:02.036819Z

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Observation ae28b156-0600-4bbd-98c6-0f858c0d0aca · outbound

This paper cites Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis

Reference 38

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This paper cites Understanding the difficulty of training deep feedforward neural networks,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Understanding the difficulty of training deep feedforward neural networks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:38:02.020544Z

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Observation dd075a05-2c73-4d34-95f6-fec4e10d74fe · outbound

This paper cites A user interface for optimizing radiologist engagement in image- data curation for artificial intelligence,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI A user interface for optimizing radiologist engagement in image- data curation for artificial intelligence,

Reference 40

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This paper cites Mutual - information-based registration of medical images: A survey,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Mutual - information-based registration of medical images: A survey,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:38:01.984702Z

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This paper cites Machine learning for medical imagin g,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Machine learning for medical imagin g,

Reference 42

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Observation 588bf3f4-05f3-4b4e-97cf-b1cb505d1f3b · outbound

This paper cites Hyperparameter importance across datasets,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Hyperparameter importance across datasets,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:38:01.952831Z

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Observation 0fead425-2f16-468a-aed1-091eee83f4e6 · outbound

This paper cites Me trics for evaluating 3D medical image segmentation: Analysis, selection, and tool,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Me trics for evaluating 3D medical image segmentation: Analysis, selection, and tool,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:38:01.936690Z

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Observation 4bf75d58-b008-4795-9025-fd206ce92540 · outbound

This paper cites Kernel Density Estimation and Classification,.

Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI Kernel Density Estimation and Classification,

Reference 45

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