Search Results - "Ruan, Su"

A review: Deep learning for medical image segmentation using multi-modality fusion by Zhou, Tongxue, Ruan, Su, Canu, Stéphane

“…Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using…”
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Automatic COVID‐19 CT segmentation using U‐Net integrated spatial and channel attention mechanism by Zhou, Tongxue, Canu, Stéphane, Ruan, Su

“…The coronavirus disease (COVID‐19) pandemic has led to a devastating effect on the global public health. Computed Tomography (CT) is an effective tool in the…”
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Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions by Chunfeng Lian, Su Ruan, Denoeux, Thierry, Hua Li, Vera, Pierre

“…Precise delineation of target tumor is a key factor to ensure the effectiveness of radiation therapy. While hybrid positron emission tomography-computed…”
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Efficient brain tumor segmentation using Swin transformer and enhanced local self-attention by Ghazouani, Fethi, Vera, Pierre, Ruan, Su

“…Purpose Fully convolutional neural networks architectures have proven to be useful for brain tumor segmentation tasks. However, their performance in learning…”
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Feature selection for outcome prediction in oesophageal cancer using genetic algorithm and random forest classifier by Paul, Desbordes, Su, Ruan, Romain, Modzelewski, Sébastien, Vauclin, Pierre, Vera, Isabelle, Gardin

“…Highlights • Proposition of a new feature selection strategy in two steps called GARF. • Selection of relevant subset of features extracted from PET images and…”
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Dissimilarity Metric Learning in the Belief Function Framework by Chunfeng Lian, Su Ruan, Denoux, Thierry

“…The evidential K-nearest-neighbor (EK-NN) method provided a global treatment of imperfect knowledge regarding the class membership of training patterns. It has…”
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Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review by Kebaili, Aghiles, Lapuyade-Lahorgue, Jérôme, Ruan, Su

“…Deep learning has become a popular tool for medical image analysis, but the limited availability of training data remains a major challenge, particularly in…”
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Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction by Lian, Chunfeng, Ruan, Su, Denœux, Thierry, Jardin, Fabrice, Vera, Pierre

“…•A stable system for cancer treatment outcome prediction is proposed.•Radiomic features extracted from FDG-PET images are used to construct the system.•Input…”
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Segmenting Multi-Source Images Using Hidden Markov Fields With Copula-Based Multivariate Statistical Distributions by Lapuyade-Lahorgue, Jérôme, Xue, Jing-Hao, Ruan, Su

“…Nowadays, multi-source image acquisition attracts an increasing interest in many fields, such as multi-modal medical image segmentation. Such acquisition aims…”
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Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET by Hongmei Mi, Petitjean, Caroline, Dubray, Bernard, Vera, Pierre, Su Ruan

“…We propose a patient-specific model based on partial differential equation to predict the evolution of lung tumors during radiotherapy. The evolution of tumor…”
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Semi-automatic lymphoma detection and segmentation using fully conditional random fields by Yu, Yuntao, Decazes, Pierre, Lapuyade-Lahorgue, Jérôme, Gardin, Isabelle, Vera, Pierre, Ruan, Su

“…•Fully Conditional Random Fields (CRF) are studied for the detection and segmentation of lymphoma from PET/CT.•Lymphomas can be everywhere in the body. CRF can…”
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Predictive value of initial FDG-PET features for treatment response and survival in esophageal cancer patients treated with chemo-radiation therapy using a random forest classifier by Desbordes, Paul, Ruan, Su, Modzelewski, Romain, Pineau, Pascal, Vauclin, Sébastien, Gouel, Pierrick, Michel, Pierre, Di Fiore, Frédéric, Vera, Pierre, Gardin, Isabelle

“…In oncology, texture features extracted from positron emission tomography with 18-fluorodeoxyglucose images (FDG-PET) are of increasing interest for predictive…”
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Weakly Supervised Tumor Detection in PET Using Class Response for Treatment Outcome Prediction by Amyar, Amine, Modzelewski, Romain, Vera, Pierre, Morard, Vincent, Ruan, Su

“…It is proven that radiomic characteristics extracted from the tumor region are predictive. The first step in radiomic analysis is the segmentation of the…”
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CUS-RF-Based Credit Card Fraud Detection with Imbalanced Data by Li, Wei, Wu, Cheng-shu, Ruan, Su-mei

“…With the continuous expansion of the banks' credit card businesses, credit card fraud has become a serious threat to banking financial institutions. So, the…”
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A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction by Brochet, Thibaud, Lapuyade-Lahorgue, Jérôme, Huat, Alexandre, Thureau, Sébastien, Pasquier, David, Gardin, Isabelle, Modzelewski, Romain, Gibon, David, Thariat, Juliette, Grégoire, Vincent, Vera, Pierre, Ruan, Su

“…In this paper, we propose to quantitatively compare loss functions based on parameterized Tsallis-Havrda-Charvat entropy and classical Shannon entropy for the…”
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Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 2022, 24 , 436 by Brochet, Thibaud, Lapuyade-Lahorgue, Jérôme, Huat, Alexandre, Thureau, Sébastien, Pasquier, David, Gardin, Isabelle, Modzelewski, Romain, Gibon, David, Thariat, Juliette, Grégoire, Vincent, Vera, Pierre, Ruan, Su

“…Alexandre Huat, Sébastien Thureau, David Pasquier, Isabelle Gardin, Romain Modzelewski, David Gibon, Juliette Thariat and Vincent Grégoire were not included as…”
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Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric by Chunfeng Lian, Su Ruan, Denoeux, Thierry, Hua Li, Vera, Pierre

“…While accurate tumor delineation in FDG-PET is a vital task, noisy and blurring imaging system makes it a challenging work. In this paper, we propose to…”
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Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images by Chunfeng Lian, Su Ruan, Denoux, Thierry, Yu Guo, Vera, Pierre

“…While hybrid PET/CT scanner is becoming a standard imaging technique in clinical oncology, many existing methods still segment tumor in mono-modality without…”
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Brain tumor segmentation from multiple MRI sequences using multiple kernel learning by Boughattas, Naouel, Berar, Maxime, Hamrouni, Kamel, Su Ruan

“…We propose a brain tumor segmentation method from multi-spectral MRI images. First, a large set of features based on wavelet coefficients, is computed on all…”
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Outcome prediction in tumour therapy based on Dempster-Shafer theory by Chunfeng Lian, Su Ruan, Denoux, Thierry, Vera, Pierre

“…Outcome prediction plays a vital role in cancer treatment. It can help to update and optimize the treatment planning. In this paper, we aim to find…”
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