Výsledky vyhľadávania - "Computer-Assisted: methods"

Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects Autor Koetzier, Lennart R, Mastrodicasa, Domenico, Szczykutowicz, Timothy P, van der Werf, Niels R, Wang, Adam S, Sandfort, Veit, van der Molen, Aart J, Fleischmann, Dominik, Willemink, Martin J

“…Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered…”
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Medical Image Segmentation Review: The Success of U-Net Autor Azad, Reza, Aghdam, Ehsan Khodapanah, Rauland, Amelie, Jia, Yiwei, Avval, Atlas Haddadi, Bozorgpour, Afshin, Karimijafarbigloo, Sanaz, Cohen, Joseph Paul, Adeli, Ehsan, Merhof, Dorit

“…Automatic medical image segmentation is a crucial topic in the medical domain and successively a critical counterpart in the computer-aided diagnosis paradigm…”
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A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets Autor Antropova, Natalia, Huynh, Benjamin Q., Giger, Maryellen L.

“…Background Deep learning methods for radiomics/computer‐aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for…”
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Radiomics: Images Are More than Pictures, They Are Data Autor Gillies, Robert J, Kinahan, Paul E, Hricak, Hedvig

“…In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data…”
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Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer Autor Steiner, David F, MacDonald, Robert, Liu, Yun, Truszkowski, Peter, Hipp, Jason D, Gammage, Christopher, Thng, Florence, Peng, Lily, Stumpe, Martin C

“…Advances in the quality of whole-slide images have set the stage for the clinical use of digital images in anatomic pathology. Along with advances in computer…”
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A survey on deep learning for skin lesion segmentation Autor Mirikharaji, Zahra, Abhishek, Kumar, Bissoto, Alceu, Barata, Catarina, Avila, Sandra, Valle, Eduardo, Celebi, M. Emre, Hamarneh, Ghassan

“…Skin cancer is a major public health problem that could benefit from computer-aided diagnosis to reduce the burden of this common disease. Skin lesion…”
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Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy Autor Urban, Gregor, Tripathi, Priyam, Alkayali, Talal, Mittal, Mohit, Jalali, Farid, Karnes, William, Baldi, Pierre

“…The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate,…”
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ChatCAD+: Toward a Universal and Reliable Interactive CAD Using LLMs Autor Zhao, Zihao, Wang, Sheng, Gu, Jinchen, Zhu, Yitao, Mei, Lanzhuju, Zhuang, Zixu, Cui, Zhiming, Wang, Qian, Shen, Dinggang

“…The integration of Computer-Aided Diagnosis (CAD) with Large Language Models (LLMs) presents a promising frontier in clinical applications, notably in…”
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Medical SAM adapter: Adapting segment anything model for medical image segmentation Autor Wu, Junde, Wang, Ziyue, Hong, Mingxuan, Ji, Wei, Fu, Huazhu, Xu, Yanwu, Xu, Min, Jin, Yueming

“…The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation…”
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A review of deep learning-based information fusion techniques for multimodal medical image classification Autor Li, Yihao, El Habib Daho, Mostafa, Conze, Pierre-Henri, Zeghlache, Rachid, Le Boité, Hugo, Tadayoni, Ramin, Cochener, Béatrice, Lamard, Mathieu, Quellec, Gwenolé

“…Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it combines information from various imaging modalities to provide a…”
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Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification Autor Al-masni, Mohammed A., Kim, Dong-Hyun, Kim, Tae-Seong

“…•An integrated two-stage diagnostic model for skin lesion boundary segmentation and multiple skin diseases classification is proposed.•Segmentation of skin…”
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Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning Autor Song, Zhigang, Zou, Shuangmei, Zhou, Weixun, Huang, Yong, Shao, Liwei, Yuan, Jing, Gou, Xiangnan, Jin, Wei, Wang, Zhanbo, Chen, Xin, Ding, Xiaohui, Liu, Jinhong, Yu, Chunkai, Ku, Calvin, Liu, Cancheng, Sun, Zhuo, Xu, Gang, Wang, Yuefeng, Zhang, Xiaoqing, Wang, Dandan, Wang, Shuhao, Xu, Wei, Davis, Richard C., Shi, Huaiyin

“…The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of…”
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Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays Autor Brunese, Luca, Mercaldo, Francesco, Reginelli, Alfonso, Santone, Antonella

“…•We show how deep learning can be applied for COVID-19 detection from chest X-rays;•The proposed method is aimed to mark as first step a chest X-ray as related…”
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Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks Autor Dar, Salman UH, Yurt, Mahmut, Karacan, Levent, Erdem, Aykut, Erdem, Erkut, Cukur, Tolga

“…Acquiring images of the same anatomy with multiple different contrasts increases the diversity of diagnostic information available in an MR exam. Yet, the scan…”
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Synthetic CT generation from MRI using 3D transformer‐based denoising diffusion model Autor Pan, Shaoyan, Abouei, Elham, Wynne, Jacob, Chang, Chih‐Wei, Wang, Tonghe, Qiu, Richard L. J., Li, Yuheng, Peng, Junbo, Roper, Justin, Patel, Pretesh, Yu, David S., Mao, Hui, Yang, Xiaofeng

“…Background and purpose Magnetic resonance imaging (MRI)‐based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by…”
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A deep learning framework for supporting the classification of breast lesions in ultrasound images Autor Han, Seokmin, Kang, Ho-Kyung, Jeong, Ja-Yeon, Park, Moon-Ho, Kim, Wonsik, Bang, Won-Chul, Seong, Yeong-Kyeong

“…In this research, we exploited the deep learning framework to differentiate the distinctive types of lesions and nodules in breast acquired with ultrasound…”
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Automatic multiorgan segmentation in thorax CT images using U‐net‐GAN Autor Dong, Xue, Lei, Yang, Wang, Tonghe, Thomas, Matthew, Tang, Leonardo, Curran, Walter J., Liu, Tian, Yang, Xiaofeng

“…Purpose Accurate and timely organs‐at‐risk (OARs) segmentation is key to efficient and high‐quality radiation therapy planning. The purpose of this work is to…”
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AI-based computer-aided diagnosis (AI-CAD): the latest review to read first Autor Fujita, Hiroshi

“…The third artificial intelligence (AI) boom is coming, and there is an inkling that the speed of its evolution is quickly increasing. In games like chess,…”
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CBCT‐Based synthetic CT image generation using conditional denoising diffusion probabilistic model Autor Peng, Junbo, Qiu, Richard L. J., Wynne, Jacob F., Chang, Chih‐Wei, Pan, Shaoyan, Wang, Tonghe, Roper, Justin, Liu, Tian, Patel, Pretesh R., Yu, David S., Yang, Xiaofeng

“…Background Daily or weekly cone‐beam computed tomography (CBCT) scans are commonly used for accurate patient positioning during the image‐guided radiotherapy…”
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Variability and reproducibility in deep learning for medical image segmentation Autor Renard, Félix, Guedria, Soulaimane, Palma, Noel De, Vuillerme, Nicolas

“…Medical image segmentation is an important tool for current clinical applications. It is the backbone of numerous clinical diagnosis methods, oncological…”
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