| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1189 | 2023 |
| Dermoscopic image segmentation via multistage fully convolutional networks L Bi, J Kim, E Ahn, A Kumar, M Fulham, D Feng IEEE Transactions on Biomedical Engineering 64 (9), 2065-2074, 2017 | 346 | 2017 |
| Automatic skin lesion analysis using large-scale dermoscopy images and deep residual networks L Bi, J Kim, E Ahn, D Feng arXiv preprint arXiv:1703.04197, 2017 | 280 | 2017 |
| Step-wise integration of deep class-specific learning for dermoscopic image segmentation L Bi, J Kim, E Ahn, A Kumar, D Feng, M Fulham Pattern recognition 85, 78-89, 2019 | 182 | 2019 |
| Synthesis of positron emission tomography (PET) images via multi-channel generative adversarial networks (GANs) L Bi, J Kim, A Kumar, D Feng, M Fulham Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and …, 2017 | 182 | 2017 |
| Saliency-based lesion segmentation via background detection in dermoscopic images E Ahn, J Kim, L Bi, A Kumar, C Li, M Fulham, DD Feng IEEE journal of biomedical and health informatics 21 (6), 1685-1693, 2017 | 163 | 2017 |
| Multimodal spatial attention module for targeting multimodal PET-CT lung tumor segmentation X Fu, L Bi, A Kumar, M Fulham, J Kim IEEE Journal of Biomedical and Health Informatics 25 (9), 3507-3516, 2021 | 120 | 2021 |
| Automatic liver lesion detection using cascaded deep residual networks L Bi, J Kim, A Kumar, D Feng arXiv preprint arXiv:1704.02703, 2017 | 100 | 2017 |
| Multi-label classification of multi-modality skin lesion via hyper-connected convolutional neural network L Bi, DD Feng, M Fulham, J Kim Pattern Recognition 107, 107502, 2020 | 92 | 2020 |
| Automated skin lesion segmentation via image-wise supervised learning and multi-scale superpixel based cellular automata L Bi, J Kim, E Ahn, D Feng, M Fulham 2016 IEEE 13th international symposium on biomedical imaging (ISBI), 1059-1062, 2016 | 90 | 2016 |
| Automatic melanoma detection via multi-scale lesion-biased representation and joint reverse classification L Bi, J Kim, E Ahn, D Feng, M Fulham 2016 IEEE 13th international symposium on biomedical imaging (ISBI), 1055-1058, 2016 | 87 | 2016 |
| Dual-path adversarial learning for fully convolutional network (FCN)-based medical image segmentation L Bi, D Feng, J Kim The Visual Computer 34, 1043-1052, 2018 | 78 | 2018 |
| Automatic detection and classification of regions of FDG uptake in whole-body PET-CT lymphoma studies L Bi, J Kim, A Kumar, L Wen, D Feng, M Fulham Computerized Medical Imaging and Graphics 60, 3-10, 2017 | 77 | 2017 |
| An overview of artificial intelligence in diabetic retinopathy and other ocular diseases B Sheng, X Chen, T Li, T Ma, Y Yang, L Bi, X Zhang Frontiers in Public Health 10, 971943, 2022 | 71 | 2022 |
| Automated saliency-based lesion segmentation in dermoscopic images E Ahn, L Bi, YH Jung, J Kim, C Li, M Fulham, DD Feng 2015 37th annual international conference of the IEEE engineering in …, 2015 | 70 | 2015 |
| Unsupervised brain tumor segmentation using a symmetric-driven adversarial network X Wu, L Bi, M Fulham, DD Feng, L Zhou, J Kim Neurocomputing 455, 242-254, 2021 | 54 | 2021 |
| Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation L Bi, J Kim, A Kumar, M Fulham, D Feng The Visual Computer 33, 1061-1071, 2017 | 53 | 2017 |
| The brain tumor sequence registration challenge: establishing correspondence between pre-operative and follow-up MRI scans of diffuse glioma patients B Baheti, D Waldmannstetter, S Chakrabarty, H Akbari, M Bilello, ... arXiv preprint arXiv:2112.06979, 2021 | 47 | 2021 |
| The autopet challenge: towards fully automated lesion segmentation in oncologic pet/ct imaging S Gatidis, M Früh, M Fabritius, S Gu, K Nikolaou, C La Fougère, J Ye, J He, ... | 43 | 2023 |
| Robust deep learning method for choroidal vessel segmentation on swept source optical coherence tomography images X Liu, L Bi, Y Xu, D Feng, J Kim, X Xu Biomedical Optics Express 10 (4), 1601-1612, 2019 | 42 | 2019 |
Jinman KimSchool of Computer Science, University of SydneyVerified email at sydney.edu.au
