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[1]K. M. Napte, A. Mahajan and S. Urooj, "Automatic Liver Cancer Detection Using Deep Convolution Neural Network," IEEE Access, vol. 11, no. 3, pp. 94852-94862, 2023, doi: 10.1109/ACCESS.2023.3307640.
[2]H. Zhang, L. Guo, J. Wang, S. Ying and J. Shi, "Multi-View Feature Transformation Based SVM+ for Computer-Aided Diagnosis of Liver Cancers With Ultrasound Images," IEEE J BIOMED HEALTH, vol. 27, no. 3, pp. 1512-1523, March 2023, doi: 10.1109/JBHI.2022.3233717.
[3]J. Moo, P. K. Marsden, K. Vyas and A. J. Reader, "Real-Time Deep-Learned Reconstruction for a Scanning Intraoperative Probe," IEEE T RADIAT PLASMA, vol. 7, no. 2, pp. 143-150, Feb. 2023, doi: 10.1109/TRPMS.2022.3209014.
[4]Y. Yan, F. Fujii, T. Shiinoki and S. Liu, "Markerless Lung Tumor Localization From Intraoperative Stereo Color Fluoroscopic Images for Radiotherapy," IEEE Access, vol. 12, no. 3, pp. 40809-40826, 2024, doi: 10.1109/ACCESS.2024.3376744.
[5]T. Bossis, M. A. Verdier, C. Trigila, L. Pinot, F. Bouvet, A. Blot, H. Ramarijaona, T. Beaumont, and D. Broggio, "A High-Resolution Portable Gamma-Camera for Estimation of Absorbed Dose in Molecular Radiotherapy," in IEEE T RADIAT PLASMA, vol. 8, no. 5, pp. 556-570, May 2024, doi: 10.1109/TRPMS.2024.3376826.
[6]Y. Fang, F. Yang, L. Tan, W. He, P. Wang and X. Ding, "An Electric Field Stereotaxis Method for Surgical Localization and Navigation of Solid Organs," IEEE SENS J, vol. 24, no. 12, pp. 19736-19744, 15 June15, 2024, doi: 10.1109/JSEN.2024.3393857.
[7]R. Zheng, Q. Wang, S. Z. Lv, C. P. Li, C. Y. Wang, W. B. Chen, and H. Wang, "Automatic Liver Tumor Segmentation on Dynamic Contrast Enhanced MRI Using 4D Information: Deep Learning Model Based on 3D Convolution and Convolutional LSTM," IEEE T MED IMAGING, vol. 41, no. 10, pp. 2965-2976, Oct. 2022, doi: 10.1109/TMI.2022.3175461.
[8]M. Hasanvand, M. Nooshyar, E. Moharamkhani, and A. Selyari. "Machine Learning Methodology for Identifying Vehicles Using Image Processing," AIA, vol. 1, no. 3, pp. 170-178, April, 2023, DOI: 10.47852/bonviewAIA3202833.
[9]A. Gautheron, M. Sdika, M. Hébert and B. Montcel, "An Explicit Estimated Baseline Model for Robust Estimation of Fluorophores Using Multiple-Wavelength Excitation Fluorescence Spectroscopy," EEE T BIO-MED ENG, vol. 71, no. 1, pp. 295-306, Jan. 2024, doi: 10.1109/TBME.2023.3299689.
[10]S. K. Singh and A. N. Yadav, "Machine Learning Approach in Optimal Localization of Tumor Using a Novel SIW-Based Antenna for Improvement of Ablation Zone in Hepatocellular Carcinoma," IEEE Access, vol. 11, pp. 26964-26978, 2023, doi: 10.1109/ACCESS.2023.3257869.
[11]A. S. Janani, S. A. Rezaeieh, A. Darvazehban, S. E. Keating and A. M. Abbosh, "Portable Electromagnetic Device for Steatotic Liver Detection Using Blind Source Separation and Shannon Wavelet Entropy," IEEE J ELECTROMAG RF, vol. 6, no. 4, pp. 546-554, Dec. 2022, doi: 10.1109/JERM.2022.3205247.
[12]D. -Y. Tu, P. -C. Lin, H. -H. Chou, M. -R. Shen and S. -Y. Hsieh, "Slice-Fusion: Reducing False Positives in Liver Tumor Detection for Mask R-CNN," IEEE ACM T COMPUT BI, vol. 20, no. 5, pp. 3267-3277, 1 Sept.-Oct. 2023, doi: 10.1109/TCBB.2023.3265394.
[13]F. Zhan, W. Wang, Q. Chen, Y. Guo, L. He and L. Wang, "Three-Direction Fusion for Accurate Volumetric Liver and Tumor Segmentation," IEEE J BIOMED HEALTH, vol. 28, no. 4, pp. 2175-2186, April 2024, doi: 10.1109/JBHI.2023.3344392.
[14]J. Amin, M. Almas Anjum, M. Sharif, S. Kadry and R. González Crespo, "Visual Geometry Group based on U-Shaped Model for Liver/Liver Tumor Segmentation," IEEE LAT AM T, vol. 21, no. 4, pp. 557-564, April 2023, doi: 10.1109/TLA.2023.10128927.
[15]P. Wan, H. Y. Xue, C. R. Liu, F. Chen, W. Shao, J. Qin, W. T. Kong, and D. Q. Zhang, "Transport-Based Anatomical-Functional Metric Learning for Liver Tumor Recognition Using Dual-View Dynamic CEUS Imaging," IEEE T BIO-MED ENG, vol. 70, no. 3, pp. 1012-1023, March 2023, doi: 10.1109/TBME.2022.3207473.
[16]S. Di, Y. -Q. Zhao, M. Liao, F. Zhang and X. Li, "TD-Net: A Hybrid End-to-End Network for Automatic Liver Tumor Segmentation From CT Images," IEEE J BIOMED HEALTH, vol. 27, no. 3, pp. 1163-1172, March 2023, doi: 10.1109/JBHI.2022.3181974.
[17]Y. Wang, C. Li and Z. Wang, "Advancing Precision Medicine: VAE Enhanced Predictions of Pancreatic Cancer Patient Survival in Local Hospital," IEEE Access, vol. 12, no. 1, pp. 3428-3436, 2024, doi: 10.1109/ACCESS.2023.3348810.
[18]J. V. N. Ramesh, T. Abirami, T. Gopalakrishnan, K. Narayanasamy, and M. K. Ishak, "Sparrow Search Algorithm With Stacked Deep Learning Based Medical Image Analysis for Pancreatic Cancer Detection and Classification," IEEE Access, vol. 11, no.2, pp. 111927-111935, 2023, doi: 10.1109/ACCESS.2023.3322376.
[19]H. Ghorpade, J. Jagtap, S. Patil, K. Kotecha, A. Abraham, N. Horvat, and J. Chakraborty, "Automatic Segmentation of Pancreas and Pancreatic Tumor: A Review of a Decade of Research," IEEE Access, vol. 11, no. 2, pp. 108727-108745, 2023, doi: 10.1109/ACCESS.2023.3320570.
[20]J. Li, H. Zhu, T. Chen and X. Qian, "Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework," IEEE J BIOMED HEALTH, vol. 27, no. 10, pp. 4780-4791, Oct. 2023, doi: 10.1109/JBHI.2023.3294278.
[21]P. Hu, X. Li, N. Lu, K. Q. Dong, X. L. Bai, T. B. Liang, and J. S. Li, "Prediction of New-Onset Diabetes After Pancreatectomy With Subspace Clustering Based Multi-View Feature Selection," IEEE J BIOMED HEALTH, vol. 27, no. 3, pp. 1588-1599, March 2023, doi: 10.1109/JBHI.2022.3233402.
[22]R. Kong, C. X. Dai, Q. Zhang, L. Gao, Z. Q. Chen, Y. T. Song, Z. J. Wu, J. M. Wang, and S. Wang, "Integrated US-OCT-NIRF Tri-Modality Endoscopic Imaging System for Pancreaticobiliary Duct Imaging," IEEE T ULTRASON FERR, vol. 69, no. 6, pp. 1970-1979, June 2022, doi: 10.1109/TUFFC.2022.3164777.
[23]H. M. Kim, S. C. Yang, J. H. Park and S. K. Lee, "Fabrication of Top–Down-Based Optical Fiber Nanoprobes and Their Diagnostic Application for Pancreatic Cancer," IEEE SENS J, vol. 24, no. 8, pp. 11966-11973, 15 April15, 2024, doi: 10.1109/JSEN.2024.3372948.
[24]J. Li, P. P. Zhang, T. Wang, L. Zhu, R. H. Liu, X. Yang, K. X. Wang, D. G. Shen, and B. Sheng, "DSMT-Net: Dual Self-Supervised Multi-Operator Transformation for Multi-Source Endoscopic Ultrasound Diagnosis," IEEE T MED IMAGING, vol. 43, no. 1, pp. 64-75, Jan. 2024, doi: 10.1109/TMI.2023.3289859.
[25]J. Li, T. Chen and X. Qian, "Generalizable Pancreas Segmentation Modeling in CT Imaging via Meta-Learning and Latent-Space Feature Flow Generation," IEEE J BIOMED HEALTH, vol. 27, no. 1, pp. 374-385, Jan. 2023, doi: 10.1109/JBHI.2022.3207597.
[26]M. Connaughton and M. Dabagh, "Modeling Physical Forces Experienced by Cancer and Stromal Cells Within Different Organ-Specific Tumor Tissue," IEEE J TRANSL ENG HE, vol. 12, pp. 413-434, 2024, doi: 10.1109/JTEHM.2024.3388561.
[27]A. Midya, J. Chakraborty, R. Srouji, R. R. Narayan, T. Boerner, J. Zheng, L. M. Pak, and M. John, "Computerized Diagnosis of Liver Tumors From CT Scans Using a Deep Neural Network Approach," IEEE J BIOMED HEALTH, vol. 27, no. 5, pp. 2456-2464, May 2023, doi: 10.1109/JBHI.2023.3248489.
[28]T. Zhang, Y. L. Feng, Y. Zhao, G. D. Fan, A. M. Yang, S. Lyu, P. Zhang, F. Song, C. B. Ma, "MSHT: Multi-Stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer," IEEE J BIOMED HEALTH, vol. 27, no. 4, pp. 1946-1957, April 2023, doi: 10.1109/JBHI.2023.3234289.
[29]K. -N. Wang, S. X. Li, Z. Bu, F. X. Zhao, G. Q. Zhou, S. J. Zhou, and Y. Chen, "SBCNet: Scale and Boundary Context Attention Dual-Branch Network for Liver Tumor Segmentation," in IEEE J BIOMED HEALTH, vol. 28, no. 5, pp. 2854-2865, May 2024, doi: 10.1109/JBHI.2024.3370864.
[30]X. Li, R. Guo, J. Lu, T. Chen and X. Qian, "Causality-Driven Graph Neural Network for Early Diagnosis of Pancreatic Cancer in Non-Contrast Computerized Tomography," IEEE T MED IMAGING, vol. 42, no. 6, pp. 1656-1667, June 2023, doi: 10.1109/TMI.2023.3236162.
[2]H. Zhang, L. Guo, J. Wang, S. Ying and J. Shi, "Multi-View Feature Transformation Based SVM+ for Computer-Aided Diagnosis of Liver Cancers With Ultrasound Images," IEEE J BIOMED HEALTH, vol. 27, no. 3, pp. 1512-1523, March 2023, doi: 10.1109/JBHI.2022.3233717.
[3]J. Moo, P. K. Marsden, K. Vyas and A. J. Reader, "Real-Time Deep-Learned Reconstruction for a Scanning Intraoperative Probe," IEEE T RADIAT PLASMA, vol. 7, no. 2, pp. 143-150, Feb. 2023, doi: 10.1109/TRPMS.2022.3209014.
[4]Y. Yan, F. Fujii, T. Shiinoki and S. Liu, "Markerless Lung Tumor Localization From Intraoperative Stereo Color Fluoroscopic Images for Radiotherapy," IEEE Access, vol. 12, no. 3, pp. 40809-40826, 2024, doi: 10.1109/ACCESS.2024.3376744.
[5]T. Bossis, M. A. Verdier, C. Trigila, L. Pinot, F. Bouvet, A. Blot, H. Ramarijaona, T. Beaumont, and D. Broggio, "A High-Resolution Portable Gamma-Camera for Estimation of Absorbed Dose in Molecular Radiotherapy," in IEEE T RADIAT PLASMA, vol. 8, no. 5, pp. 556-570, May 2024, doi: 10.1109/TRPMS.2024.3376826.
[6]Y. Fang, F. Yang, L. Tan, W. He, P. Wang and X. Ding, "An Electric Field Stereotaxis Method for Surgical Localization and Navigation of Solid Organs," IEEE SENS J, vol. 24, no. 12, pp. 19736-19744, 15 June15, 2024, doi: 10.1109/JSEN.2024.3393857.
[7]R. Zheng, Q. Wang, S. Z. Lv, C. P. Li, C. Y. Wang, W. B. Chen, and H. Wang, "Automatic Liver Tumor Segmentation on Dynamic Contrast Enhanced MRI Using 4D Information: Deep Learning Model Based on 3D Convolution and Convolutional LSTM," IEEE T MED IMAGING, vol. 41, no. 10, pp. 2965-2976, Oct. 2022, doi: 10.1109/TMI.2022.3175461.
[8]M. Hasanvand, M. Nooshyar, E. Moharamkhani, and A. Selyari. "Machine Learning Methodology for Identifying Vehicles Using Image Processing," AIA, vol. 1, no. 3, pp. 170-178, April, 2023, DOI: 10.47852/bonviewAIA3202833.
[9]A. Gautheron, M. Sdika, M. Hébert and B. Montcel, "An Explicit Estimated Baseline Model for Robust Estimation of Fluorophores Using Multiple-Wavelength Excitation Fluorescence Spectroscopy," EEE T BIO-MED ENG, vol. 71, no. 1, pp. 295-306, Jan. 2024, doi: 10.1109/TBME.2023.3299689.
[10]S. K. Singh and A. N. Yadav, "Machine Learning Approach in Optimal Localization of Tumor Using a Novel SIW-Based Antenna for Improvement of Ablation Zone in Hepatocellular Carcinoma," IEEE Access, vol. 11, pp. 26964-26978, 2023, doi: 10.1109/ACCESS.2023.3257869.
[11]A. S. Janani, S. A. Rezaeieh, A. Darvazehban, S. E. Keating and A. M. Abbosh, "Portable Electromagnetic Device for Steatotic Liver Detection Using Blind Source Separation and Shannon Wavelet Entropy," IEEE J ELECTROMAG RF, vol. 6, no. 4, pp. 546-554, Dec. 2022, doi: 10.1109/JERM.2022.3205247.
[12]D. -Y. Tu, P. -C. Lin, H. -H. Chou, M. -R. Shen and S. -Y. Hsieh, "Slice-Fusion: Reducing False Positives in Liver Tumor Detection for Mask R-CNN," IEEE ACM T COMPUT BI, vol. 20, no. 5, pp. 3267-3277, 1 Sept.-Oct. 2023, doi: 10.1109/TCBB.2023.3265394.
[13]F. Zhan, W. Wang, Q. Chen, Y. Guo, L. He and L. Wang, "Three-Direction Fusion for Accurate Volumetric Liver and Tumor Segmentation," IEEE J BIOMED HEALTH, vol. 28, no. 4, pp. 2175-2186, April 2024, doi: 10.1109/JBHI.2023.3344392.
[14]J. Amin, M. Almas Anjum, M. Sharif, S. Kadry and R. González Crespo, "Visual Geometry Group based on U-Shaped Model for Liver/Liver Tumor Segmentation," IEEE LAT AM T, vol. 21, no. 4, pp. 557-564, April 2023, doi: 10.1109/TLA.2023.10128927.
[15]P. Wan, H. Y. Xue, C. R. Liu, F. Chen, W. Shao, J. Qin, W. T. Kong, and D. Q. Zhang, "Transport-Based Anatomical-Functional Metric Learning for Liver Tumor Recognition Using Dual-View Dynamic CEUS Imaging," IEEE T BIO-MED ENG, vol. 70, no. 3, pp. 1012-1023, March 2023, doi: 10.1109/TBME.2022.3207473.
[16]S. Di, Y. -Q. Zhao, M. Liao, F. Zhang and X. Li, "TD-Net: A Hybrid End-to-End Network for Automatic Liver Tumor Segmentation From CT Images," IEEE J BIOMED HEALTH, vol. 27, no. 3, pp. 1163-1172, March 2023, doi: 10.1109/JBHI.2022.3181974.
[17]Y. Wang, C. Li and Z. Wang, "Advancing Precision Medicine: VAE Enhanced Predictions of Pancreatic Cancer Patient Survival in Local Hospital," IEEE Access, vol. 12, no. 1, pp. 3428-3436, 2024, doi: 10.1109/ACCESS.2023.3348810.
[18]J. V. N. Ramesh, T. Abirami, T. Gopalakrishnan, K. Narayanasamy, and M. K. Ishak, "Sparrow Search Algorithm With Stacked Deep Learning Based Medical Image Analysis for Pancreatic Cancer Detection and Classification," IEEE Access, vol. 11, no.2, pp. 111927-111935, 2023, doi: 10.1109/ACCESS.2023.3322376.
[19]H. Ghorpade, J. Jagtap, S. Patil, K. Kotecha, A. Abraham, N. Horvat, and J. Chakraborty, "Automatic Segmentation of Pancreas and Pancreatic Tumor: A Review of a Decade of Research," IEEE Access, vol. 11, no. 2, pp. 108727-108745, 2023, doi: 10.1109/ACCESS.2023.3320570.
[20]J. Li, H. Zhu, T. Chen and X. Qian, "Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework," IEEE J BIOMED HEALTH, vol. 27, no. 10, pp. 4780-4791, Oct. 2023, doi: 10.1109/JBHI.2023.3294278.
[21]P. Hu, X. Li, N. Lu, K. Q. Dong, X. L. Bai, T. B. Liang, and J. S. Li, "Prediction of New-Onset Diabetes After Pancreatectomy With Subspace Clustering Based Multi-View Feature Selection," IEEE J BIOMED HEALTH, vol. 27, no. 3, pp. 1588-1599, March 2023, doi: 10.1109/JBHI.2022.3233402.
[22]R. Kong, C. X. Dai, Q. Zhang, L. Gao, Z. Q. Chen, Y. T. Song, Z. J. Wu, J. M. Wang, and S. Wang, "Integrated US-OCT-NIRF Tri-Modality Endoscopic Imaging System for Pancreaticobiliary Duct Imaging," IEEE T ULTRASON FERR, vol. 69, no. 6, pp. 1970-1979, June 2022, doi: 10.1109/TUFFC.2022.3164777.
[23]H. M. Kim, S. C. Yang, J. H. Park and S. K. Lee, "Fabrication of Top–Down-Based Optical Fiber Nanoprobes and Their Diagnostic Application for Pancreatic Cancer," IEEE SENS J, vol. 24, no. 8, pp. 11966-11973, 15 April15, 2024, doi: 10.1109/JSEN.2024.3372948.
[24]J. Li, P. P. Zhang, T. Wang, L. Zhu, R. H. Liu, X. Yang, K. X. Wang, D. G. Shen, and B. Sheng, "DSMT-Net: Dual Self-Supervised Multi-Operator Transformation for Multi-Source Endoscopic Ultrasound Diagnosis," IEEE T MED IMAGING, vol. 43, no. 1, pp. 64-75, Jan. 2024, doi: 10.1109/TMI.2023.3289859.
[25]J. Li, T. Chen and X. Qian, "Generalizable Pancreas Segmentation Modeling in CT Imaging via Meta-Learning and Latent-Space Feature Flow Generation," IEEE J BIOMED HEALTH, vol. 27, no. 1, pp. 374-385, Jan. 2023, doi: 10.1109/JBHI.2022.3207597.
[26]M. Connaughton and M. Dabagh, "Modeling Physical Forces Experienced by Cancer and Stromal Cells Within Different Organ-Specific Tumor Tissue," IEEE J TRANSL ENG HE, vol. 12, pp. 413-434, 2024, doi: 10.1109/JTEHM.2024.3388561.
[27]A. Midya, J. Chakraborty, R. Srouji, R. R. Narayan, T. Boerner, J. Zheng, L. M. Pak, and M. John, "Computerized Diagnosis of Liver Tumors From CT Scans Using a Deep Neural Network Approach," IEEE J BIOMED HEALTH, vol. 27, no. 5, pp. 2456-2464, May 2023, doi: 10.1109/JBHI.2023.3248489.
[28]T. Zhang, Y. L. Feng, Y. Zhao, G. D. Fan, A. M. Yang, S. Lyu, P. Zhang, F. Song, C. B. Ma, "MSHT: Multi-Stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer," IEEE J BIOMED HEALTH, vol. 27, no. 4, pp. 1946-1957, April 2023, doi: 10.1109/JBHI.2023.3234289.
[29]K. -N. Wang, S. X. Li, Z. Bu, F. X. Zhao, G. Q. Zhou, S. J. Zhou, and Y. Chen, "SBCNet: Scale and Boundary Context Attention Dual-Branch Network for Liver Tumor Segmentation," in IEEE J BIOMED HEALTH, vol. 28, no. 5, pp. 2854-2865, May 2024, doi: 10.1109/JBHI.2024.3370864.
[30]X. Li, R. Guo, J. Lu, T. Chen and X. Qian, "Causality-Driven Graph Neural Network for Early Diagnosis of Pancreatic Cancer in Non-Contrast Computerized Tomography," IEEE T MED IMAGING, vol. 42, no. 6, pp. 1656-1667, June 2023, doi: 10.1109/TMI.2023.3236162.
Objavljeno
2025/03/24
Broj časopisa
Rubrika
Original paper
Sva prava zadržana (c) 2025 Xin Jia, Zongliang Jiang
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