Expression of Concern: Anomaly Detection in Skull scanning Images based on Multi-sensor Fusion
DOI:
https://doi.org/10.4108/eetpht.11.5828Keywords:
Skull scanning images, Bilateral filter, Double domain decomposition, High and low frequency fusion, Deep neural networksAbstract
Concerns have been raised about the reliability of the references in this manuscript due to an unusual citation pattern. The full notice can be found here: 10.4108/eetpht.11.15403
Downloads
References
[1] Wen C, Liu S, Liu S, et al. ACSN: Attention capsule sampling network for diagnosing COVID-19 based on chest CT scans[J]. Computers in Biology and Medicine, 2023, 153: 106338
[2] Sun L, Peng R. The value of integration of bone scan and targeted SPECT/CT in diagnosis of primary hyperparathyroidism with multiple bone brown tumor[J]. Skeletal radiology, 2023,52(12):2505-2511.
[3] Saidi B, Fallahi B, Haghighi F, et al. Three-phase 99mTc-MDP bone scan in a case of pigment villonodular synovitis[J]. Iranian Journal of Nuclear Medicine, 2021(156). https://readpaper.com/paper/3130285393.
[4] Zhang Y, Satapathy S C, Guttery D S, et al. Improved breast cancer classification through combining graph convolutional network and convolutional neural network[J], Information Processing and Management, 2021, 58(2), 102439
[5] Xiao Y, Xia K, Yin H, et al. AFSTGCN: prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network[J]. Digital Communications and Networks, 2024, 10(2): 292-303,
[6] Feo M D, Frantellizzi V, Rocco A D, et al. Evaluation of Bone Scan Index as a Prognostic Tool in Breast Cancer Patients with Bone Metastasis[J]. Current radiopharmaceuticals, 2023,16(4):284-291.
[7] Hiddema L, Muthusami A, Brookes P, et al. 41Diagnosing Bone Metastases in Breast Cancer – CT Vs Nuclear Medicine Bone Scan[J]. British Journal of Surgery, 2021, 108(Supplement_2), znab135.024.
[8] Song L, Liu X, Chen S, et al. A deep fuzzy model for diagnosis of COVID-19 from CT images[J]. Applied Soft Computing, 2022, 122: 108883
[9] Meyers J L, Cardoso H F V. Reliability of wet versus dry bone CT scan-based quantification of cortical area measurements[J]. American Journal of Physical Anthropology, 2021, 174(Suppl.71): 71-71.
[10] Malloy P, Newhouse A C, Alejandro A. Espinoza Orías,et al. MRI‐- and CT‐-based metrics for the quantification of arthroscopic bone resections in femoroacetabular impingement syndrome[J]. Journal of Orthopaedic Research, 2022, 40(5): 1174-1181.
[11] Banday S A, Nahvi R, Mir A H, et al. Ground glass opacity detection and segmentation using CT images: an image statistics framework[J]. IET image processing, 2022, 16(9): 2432-2445.
[12] Heidari A, Javaheri D, Toumaj S, et al. A new lung cancer detection method based on the chest CT images using Federated Learning and blockchain systems[J]. Artificial intelligence in medicine, 2023, 141(7): 1.
[13] Li Z, Zhao Z, Lian S. YOLOv5x deep learning network model based on SPECT whole body bone scanning for diagnosing benign and malignant bone lesions[J]. Chinese Journal of Medical Imaging Technology, 2023, 39(12): 1867-1871.
[14] Chen J, Wee L, Dekker A, et al. Using 3D deep features from CT scans for cancer prognosis based on a video classification model: A multi‐dataset feasibility study[J]. Medical physics, 2023, 50(7): 4220-4233.
[15] Cerci J J, Fanti S, Lobato E E et al. Diagnostic Performance and Clinical Impact of Ga-68-PSMA-11 PET/CT Imaging in Early Relapsed Prostate Cancer After Radical Therapy: A Prospective Multicenter Study (IAEA-PSMA Study)[J]. The Journal of Nuclear Medicine, 2022, 63(2): 240-247.
[16] Rashid R, Zhang E, Abdi A. Some measured frequency domain characteristics of the underwater vector and scalar acoustic field components with applications to communication receivers[J]. The Journal of the Acoustical Society of America, 2021, 150(4): A155.
[17] Liu X, Hou S, Liu S, et al. Attention-based Multimodal Glioma Segmentation with Multi-attention Layers for Small-intensity Dissimilarity[J]. Journal of King Saud University - Computer and Information Sciences, 2023, 35: 183-195
[18] Manikandan L C, Selvakumar R K, Nair S A H, et al. Hardware implementation of fast bilateral filter and canny edge detector using Raspberry Pi for telemedicine applications[J]. Journal of Ambient Intelligence and Humanized Computing, 2021, 12(5): 4689-4695.
[19] Geetha V, Anbumani V, Murugesan G, et al. Hybrid optimal algorithm-based 2D discrete wavelet transform for image compression using fractional KCA[J]. Multimedia Systems, 2020, 26(8): 1-16.
[20] Han H, Wang X. Fast Multi-Sensor Information Fusion Based on Deep Hybrid Convolution[J]. Computer Simulation, 2022, 39(05): 288-291+298.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Xiaochun Guo, Hashim Ali
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
