Maxine Tan
Orcid: 0000-0001-5071-2477
According to our database1,
Maxine Tan
authored at least 32 papers
between 2009 and 2026.
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Bibliography
2026
A new time-decay radiomics integrated network (TRINet) for breast cancer risk prediction.
Medical Image Anal., 2026
2023
RADIFUSION: A multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement.
CoRR, 2023
2022
ProCAN: Progressive growing channel attentive non-local network for lung nodule classification.
Pattern Recognit., 2022
2021
Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment.
Medical Biol. Eng. Comput., 2021
CASPIANET++: A multidimensional Channel-Spatial Asymmetric attention network with Noisy Student Curriculum Learning paradigm for brain tumor segmentation.
Comput. Biol. Medicine, 2021
Int. J. Comput. Assist. Radiol. Surg., 2021
2020
2019
Cribriform pattern detection in prostate histopathological images using deep learning models.
CoRR, 2019
Int. J. Comput. Assist. Radiol. Surg., 2019
2016
A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration.
IEEE Trans. Medical Imaging, 2016
Fusion of Quantitative Image and Genomic Biomarkers to Improve Prognosis Assessment of Early Stage Lung Cancer Patients.
IEEE Trans. Biomed. Eng., 2016
A B-spline image registration based CAD scheme to evaluate drug treatment response of ovarian cancer patients.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Increasing cancer detection yield of breast MRI using a new CAD scheme of mammograms.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Computer-aided classification of mammographic masses using the deep learning technology: a preliminary study.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Computer-aided global breast MR image feature analysis for prediction of tumor response to chemotherapy: performance assessment.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
2015
An automated approach to improve efficacy in detecting residual malignant cancer cell for facilitating prognostic assessment of leukemia: an initial study.
Proceedings of the Medical Imaging 2015: Digital Pathology, 2015
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Association of mammographic image feature change and an increasing risk trend of developing breast cancer: an assessment.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Automated detection of breast tumor in MRI and comparison of kinetic features for assessing tumor response to chemotherapy.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
A new application of electrical impedance spectroscopy for measuring glucose metabolism: a phantom study.
Proceedings of the Medical Imaging 2015: Biomedical Applications in Molecular, 2015
2014
Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model.
Int. J. Comput. Assist. Radiol. Surg., 2014
A new mass classification system derived from multiple features and a trained MLP model.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, 2014
2013
Phased searching with NEAT in a Time-Scaled Framework: Experiments on a computer-aided detection system for lung nodules.
Artif. Intell. Medicine, 2013
2012
Analysis of a feature-deselective neuroevolution classifier (FD-NEAT) in a computer-aided lung nodule detection system for CT images.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012
2011
Proceedings of the 18th IEEE International Conference on Image Processing, 2011
Accelerometer based Gait Analysis - Multi Variate Assessment of Fall Risk with FD-NEAT.
Proceedings of the BIOSIGNALS 2011, 2011
2009