Suchergebnisse - "Computer aided detection"

Deep learning in medical imaging and radiation therapy von Sahiner, Berkman, Pezeshk, Aria, Hadjiiski, Lubomir M., Wang, Xiaosong, Drukker, Karen, Cha, Kenny H., Summers, Ronald M., Giger, Maryellen L.

“… The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify …”
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Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial) von Glissen Brown, Jeremy R, Mansour, Nabil M, Wang, Pu, Chuchuca, Maria Aguilera, Minchenberg, Scott B, Chandnani, Madhuri, Liu, Lin, Gross, Seth A, Sengupta, Neil, Berzin, Tyler M

“… Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect …”
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Automatic breast lesion detection in ultrafast DCE‐MRI using deep learning von Ayatollahi, Fazael, Shokouhi, Shahriar B., Mann, Ritse M., Teuwen, Jonas

“… Purpose We propose a deep learning‐based computer‐aided detection (CADe) method to detect breast lesions in ultrafast DCE‐MRI sequences. This method uses both …”
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Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets von Cha, Kenny H., Hadjiiski, Lubomir, Samala, Ravi K., Chan, Heang-Ping, Caoili, Elaine M., Cohan, Richard H.

“… Purpose: The authors are developing a computerized system for bladder segmentation in CT urography (CTU) as a critical component for computer-aided detection …”
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Effect of computer‐aided colonoscopy on adenoma miss rates and polyp detection: A systematic review and meta‐analysis von Shah, Sagar, Park, Nathan, Chehade, Nabil El Hage, Chahine, Anastasia, Monachese, Marc, Tiritilli, Amelie, Moosvi, Zain, Ortizo, Ronald, Samarasena, Jason

“… Background and Aim Multiple computer‐aided techniques utilizing artificial intelligence (AI) have been created to improve the detection of polyps during …”
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Development and Validation of a Deep Learning–based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs von Hwang, Eui Jin, Park, Sunggyun, Jin, Kwang-Nam, Kim, Jung Im, Choi, So Young, Lee, Jong Hyuk, Goo, Jin Mo, Aum, Jaehong, Yim, Jae-Joon, Park, Chang Min

“… Abstract Background Detection of active pulmonary tuberculosis on chest radiographs (CRs) is critical for the diagnosis and screening of tuberculosis. An …”
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Evaluating false‐positive detection in a computer‐aided detection system for colonoscopy von Okumura, Taishi, Imai, Kenichiro, Misawa, Masashi, Kudo, Shin‐ei, Hotta, Kinichi, Ito, Sayo, Kishida, Yoshihiro, Takada, Kazunori, Kawata, Noboru, Maeda, Yuki, Yoshida, Masao, Yamamoto, Yoichi, Minamide, Tatsunori, Ishiwatari, Hirotoshi, Sato, Junya, Matsubayashi, Hiroyuki, Ono, Hiroyuki

“… Background and Aim Computer‐aided detection (CADe) systems can efficiently detect polyps during colonoscopy. However, false‐positive (FP) activation is a major …”
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Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography von Samala, Ravi K., Chan, Heang-Ping, Hadjiiski, Lubomir, Helvie, Mark A., Wei, Jun, Cha, Kenny

“… Purpose: Develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) volume using a deep convolutional neural network …”
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MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection von Cameron, Andrew, Khalvati, Farzad, Haider, Masoom A., Wong, Alexander

“… This paper presents a quantitative radiomics feature model for performing prostate cancer detection using multiparametric MRI (mpMRI). It incorporates a novel …”
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U‐Net based deep learning bladder segmentation in CT urography von Ma, Xiangyuan, Hadjiiski, Lubomir M., Wei, Jun, Chan, Heang‐Ping, Cha, Kenny H., Cohan, Richard H., Caoili, Elaine M., Samala, Ravi, Zhou, Chuan, Lu, Yao

“… Objectives To develop a U‐Net–based deep learning approach (U‐DL) for bladder segmentation in computed tomography urography (CTU) as a part of a …”
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Automatic detection of pulmonary embolism in computed tomography pulmonary angiography using Scaled‐YOLOv4 von Xu, Haijun, Li, Huiyao, Xu, Qifei, Zhang, Zewei, Wang, Ping, Li, Dong, Guo, Li

“… Background Pulmonary embolism (PE) is a common but fatal clinical condition and the gold standard of diagnosis is computed tomography pulmonary angiography …”
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ET-NET: an ensemble of transfer learning models for prediction of COVID-19 infection through chest CT-scan images von Kundu, Rohit, Singh, Pawan Kumar, Ferrara, Massimiliano, Ahmadian, Ali, Sarkar, Ram

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Characterization of focal EEG signals: A review von Acharya, U. Rajendra, Hagiwara, Yuki, Deshpande, Sunny Nitin, Suren, S., Koh, Joel En Wei, Oh, Shu Lih, Arunkumar, N., Ciaccio, Edward J., Lim, Choo Min

“… Epilepsy is a common neurological condition that can occur in anyone at any age. Electroencephalogram (EEG) signals of non-focal (NF) and focal (F) types …”
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Artificial Intelligence in Colorectal Cancer Screening, Diagnosis and Treatment. A New Era von Mitsala, Athanasia, Tsalikidis, Christos, Pitiakoudis, Michail, Simopoulos, Constantinos, Tsaroucha, Alexandra K.

“… The development of artificial intelligence (AI) algorithms has permeated the medical field with great success. The widespread use of AI technology in …”
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MRI‐Based Breast Cancer Classification and Localization by Multiparametric Feature Extraction and Combination Using Deep Learning von Cong, Chao, Li, Xiaoguang, Zhang, Chunlai, Zhang, Jing, Sun, Kaixiang, Liu, Lianluyi, Ambale‐Venkatesh, Bharath, Chen, Xiao, Wang, Yi

“… Background Deep learning (DL) have been reported feasible in breast MRI. However, the effectiveness of DL method in mpMRI combinations for breast cancer …”
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Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique von Teramoto, Atsushi, Fujita, Hiroshi, Yamamuro, Osamu, Tamaki, Tsuneo

“… Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; …”
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Deep convolutional neural networks for multiplanar lung nodule detection: Improvement in small nodule identification von Zheng, Sunyi, Cornelissen, Ludo J., Cui, Xiaonan, Jing, Xueping, Veldhuis, Raymond N. J., Oudkerk, Matthijs, Ooijen, Peter M. A.

“… Purpose Early detection of lung cancer is of importance since it can increase patients’ chances of survival. To detect nodules accurately during screening, …”
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Automatically discriminating and localizing COVID-19 from community-acquired pneumonia on chest X-rays von Wang, Zheng, Xiao, Ying, Li, Yong, Zhang, Jie, Lu, Fanggen, Hou, Muzhou, Liu, Xiaowei

“… •We proposed a novel framework, CHP-Net, to differentiate and localize COVID-19 from community acquired pneumonia.•We used excessive data augmentation to …”
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SAtUNet: Series atrous convolution enhanced U‐Net for lung nodule segmentation von Selvadass, Salomi, Bruntha, P. Malin, Sagayam, K. Martin, Günerhan, Hatıra

“… Precise and unambiguous segmentation of pulmonary nodules from the CT images is imperative for a CAD framework implementation delineated for the prognosis of …”
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Diagnostic Performance of an Artificial Intelligence System in Breast Ultrasound von O'Connell, Avice M, Bartolotta, Tommaso V, Orlando, Alessia, Jung, Sin-Ho, Baek, Jihye, Parker, Kevin J

“… We study the performance of an artificial intelligence (AI) program designed to assist radiologists in the diagnosis of breast cancer, relative to measures …”
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