Search Results - "IEEE transactions on medical imaging"

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation by Zhou, Zongwei, Siddiquee, Md Mahfuzur Rahman, Tajbakhsh, Nima, Liang, Jianming

“…The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models…”
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Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images by Fan, Deng-Ping, Zhou, Tao, Ji, Ge-Peng, Zhou, Yi, Chen, Geng, Fu, Huazhu, Shen, Jianbing, Shao, Ling

“…Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung…”
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CE-Net: Context Encoder Network for 2D Medical Image Segmentation by Gu, Zaiwang, Cheng, Jun, Fu, Huazhu, Zhou, Kang, Hao, Huaying, Zhao, Yitian, Zhang, Tianyang, Gao, Shenghua, Liu, Jiang

“…Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing,…”
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Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets by Oh, Yujin, Park, Sangjoon, Ye, Jong Chul

“…Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-ray (CXR) image for COVID-19 diagnosis and patient triage is…”
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VoxelMorph: A Learning Framework for Deformable Medical Image Registration by Balakrishnan, Guha, Zhao, Amy, Sabuncu, Mert R., Guttag, John, Dalca, Adrian V.

“…We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical image registration. Traditional registration methods optimize an…”
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A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT by Wang, Xinggang, Deng, Xianbo, Fu, Qing, Zhou, Qiang, Feng, Jiapei, Ma, Hui, Liu, Wenyu, Zheng, Chuansheng

“…Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based…”
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Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound by Roy, Subhankar, Menapace, Willi, Oei, Sebastiaan, Luijten, Ben, Fini, Enrico, Saltori, Cristiano, Huijben, Iris, Chennakeshava, Nishith, Mento, Federico, Sentelli, Alessandro, Peschiera, Emanuele, Trevisan, Riccardo, Maschietto, Giovanni, Torri, Elena, Inchingolo, Riccardo, Smargiassi, Andrea, Soldati, Gino, Rota, Paolo, Passerini, Andrea, van Sloun, Ruud J. G., Ricci, Elisa, Demi, Libertario

“…Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based…”
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Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? by Bernard, Olivier, Lalande, Alain, Zotti, Clement, Cervenansky, Frederick, Yang, Xin, Heng, Pheng-Ann, Cetin, Irem, Lekadir, Karim, Camara, Oscar, Gonzalez Ballester, Miguel Angel, Sanroma, Gerard, Napel, Sandy, Petersen, Steffen, Tziritas, Georgios, Grinias, Elias, Khened, Mahendra, Kollerathu, Varghese Alex, Krishnamurthi, Ganapathy, Rohe, Marc-Michel, Pennec, Xavier, Sermesant, Maxime, Isensee, Fabian, Jager, Paul, Maier-Hein, Klaus H., Full, Peter M., Wolf, Ivo, Engelhardt, Sandy, Baumgartner, Christian F., Koch, Lisa M., Wolterink, Jelmer M., Isgum, Ivana, Jang, Yeonggul, Hong, Yoonmi, Patravali, Jay, Jain, Shubham, Humbert, Olivier, Jodoin, Pierre-Marc

“…Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common…”
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Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge by Campello, Victor M., Gkontra, Polyxeni, Izquierdo, Cristian, Martin-Isla, Carlos, Sojoudi, Alireza, Full, Peter M., Maier-Hein, Klaus, Zhang, Yao, He, Zhiqiang, Ma, Jun, Parreno, Mario, Albiol, Alberto, Kong, Fanwei, Shadden, Shawn C., Acero, Jorge Corral, Sundaresan, Vaanathi, Saber, Mina, Elattar, Mustafa, Li, Hongwei, Menze, Bjoern, Khader, Firas, Haarburger, Christoph, Scannell, Cian M., Veta, Mitko, Carscadden, Adam, Punithakumar, Kumaradevan, Liu, Xiao, Tsaftaris, Sotirios A., Huang, Xiaoqiong, Yang, Xin, Li, Lei, Zhuang, Xiahai, Vilades, David, Descalzo, Martin L., Guala, Andrea, Mura, Lucia La, Friedrich, Matthias G., Garg, Ria, Lebel, Julie, Henriques, Filipe, Karakas, Mahir, Cavus, Ersin, Petersen, Steffen E., Escalera, Sergio, Segui, Santi, Rodriguez-Palomares, Jose F., Lekadir, Karim

“…The emergence of deep learning has considerably advanced the state-of-the-art in cardiac magnetic resonance (CMR) segmentation. Many techniques have been…”
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MoDL: Model-Based Deep Learning Architecture for Inverse Problems by Aggarwal, Hemant K., Mani, Merry P., Jacob, Mathews

“…We introduce a model-based image reconstruction framework with a convolution neural network (CNN)-based regularization prior. The proposed formulation provides…”
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Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss by Yang, Qingsong, Yan, Pingkun, Zhang, Yanbo, Yu, Hengyong, Shi, Yongyi, Mou, Xuanqin, Kalra, Mannudeep K., Zhang, Yi, Sun, Ling, Wang, Ge

“…The continuous development and extensive use of computed tomography (CT) in medical practice has raised a public concern over the associated radiation dose to…”
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CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation by Gu, Ran, Wang, Guotai, Song, Tao, Huang, Rui, Aertsen, Michael, Deprest, Jan, Ourselin, Sebastien, Vercauteren, Tom, Zhang, Shaoting

“…Accurate medical image segmentation is essential for diagnosis and treatment planning of diseases. Convolutional Neural Networks (CNNs) have achieved…”
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A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images by Wang, Guotai, Liu, Xinglong, Li, Chaoping, Xu, Zhiyong, Ruan, Jiugen, Zhu, Haifeng, Meng, Tao, Li, Kang, Huang, Ning, Zhang, Shaoting

“…Segmentation of pneumonia lesions from CT scans of COVID-19 patients is important for accurate diagnosis and follow-up. Deep learning has a potential to…”
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Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening by Wu, Nan, Phang, Jason, Park, Jungkyu, Shen, Yiqiu, Huang, Zhe, Zorin, Masha, Jastrzebski, Stanislaw, Fevry, Thibault, Katsnelson, Joe, Kim, Eric, Wolfson, Stacey, Parikh, Ujas, Gaddam, Sushma, Lin, Leng Leng Young, Ho, Kara, Weinstein, Joshua D., Reig, Beatriu, Gao, Yiming, Toth, Hildegard, Pysarenko, Kristine, Lewin, Alana, Lee, Jiyon, Airola, Krystal, Mema, Eralda, Chung, Stephanie, Hwang, Esther, Samreen, Naziya, Kim, S. Gene, Heacock, Laura, Moy, Linda, Cho, Kyunghyun, Geras, Krzysztof J.

“…We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200000 exams (over 1000000…”
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Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis by Chen, Richard J., Lu, Ming Y., Wang, Jingwen, Williamson, Drew F. K., Rodig, Scott J., Lindeman, Neal I., Mahmood, Faisal

“…Cancer diagnosis, prognosis, mymargin and therapeutic response predictions are based on morphological information from histology slides and molecular profiles…”
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Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network by Chen, Hu, Zhang, Yi, Kalra, Mannudeep K., Lin, Feng, Chen, Yang, Liao, Peixi, Zhou, Jiliu, Wang, Ge

“…Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main…”
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A Multi-Organ Nucleus Segmentation Challenge by Kumar, Neeraj, Verma, Ruchika, Anand, Deepak, Zhou, Yanning, Onder, Omer Fahri, Tsougenis, Efstratios, Chen, Hao, Heng, Pheng-Ann, Li, Jiahui, Hu, Zhiqiang, Wang, Yunzhi, Koohbanani, Navid Alemi, Jahanifar, Mostafa, Tajeddin, Neda Zamani, Gooya, Ali, Rajpoot, Nasir, Ren, Xuhua, Zhou, Sihang, Wang, Qian, Shen, Dinggang, Yang, Cheng-Kun, Weng, Chi-Hung, Yu, Wei-Hsiang, Yeh, Chao-Yuan, Yang, Shuang, Xu, Shuoyu, Yeung, Pak Hei, Sun, Peng, Mahbod, Amirreza, Schaefer, Gerald, Ellinger, Isabella, Ecker, Rupert, Smedby, Orjan, Wang, Chunliang, Chidester, Benjamin, Ton, That-Vinh, Tran, Minh-Triet, Ma, Jian, Do, Minh N., Graham, Simon, Vu, Quoc Dang, Kwak, Jin Tae, Gunda, Akshaykumar, Chunduri, Raviteja, Hu, Corey, Zhou, Xiaoyang, Lotfi, Dariush, Safdari, Reza, Kascenas, Antanas, O'Neil, Alison, Eschweiler, Dennis, Stegmaier, Johannes, Cui, Yanping, Yin, Baocai, Chen, Kailin, Tian, Xinmei, Gruening, Philipp, Barth, Erhardt, Arbel, Elad, Remer, Itay, Ben-Dor, Amir, Sirazitdinova, Ekaterina, Kohl, Matthias, Braunewell, Stefan, Li, Yuexiang, Xie, Xinpeng, Shen, Linlin, Ma, Jun, Baksi, Krishanu Das, Khan, Mohammad Azam, Choo, Jaegul, Colomer, Adrian, Naranjo, Valery, Pei, Linmin, Iftekharuddin, Khan M., Roy, Kaushiki, Bhattacharjee, Debotosh, Pedraza, Anibal, Bueno, Maria Gloria, Devanathan, Sabarinathan, Radhakrishnan, Saravanan, Koduganty, Praveen, Wu, Zihan, Cai, Guanyu, Liu, Xiaojie, Wang, Yuqin, Sethi, Amit

“…Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology…”
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Attention Residual Learning for Skin Lesion Classification by Zhang, Jianpeng, Xie, Yutong, Xia, Yong, Shen, Chunhua

“…Automated skin lesion classification in dermoscopy images is an essential way to improve the diagnostic performance and reduce melanoma deaths. Although deep…”
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Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia by Ouyang, Xi, Huo, Jiayu, Xia, Liming, Shan, Fei, Liu, Jun, Mo, Zhanhao, Yan, Fuhua, Ding, Zhongxiang, Yang, Qi, Song, Bin, Shi, Feng, Yuan, Huan, Wei, Ying, Cao, Xiaohuan, Gao, Yaozong, Wu, Dijia, Wang, Qian, Shen, Dinggang

“…The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and…”
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Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation by Fu, Huazhu, Cheng, Jun, Xu, Yanwu, Wong, Damon Wing Kee, Liu, Jiang, Cao, Xiaochun

“…Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio (CDR) plays an important role in the screening and diagnosis of…”
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