標(biāo)題: Titlebook: Deep Learning and Medical Applications; Jin Keun Seo Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive license to [打印本頁] 作者: intensify 時間: 2025-3-21 19:47
書目名稱Deep Learning and Medical Applications影響因子(影響力)
書目名稱Deep Learning and Medical Applications影響因子(影響力)學(xué)科排名
書目名稱Deep Learning and Medical Applications網(wǎng)絡(luò)公開度
書目名稱Deep Learning and Medical Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Deep Learning and Medical Applications被引頻次
書目名稱Deep Learning and Medical Applications被引頻次學(xué)科排名
書目名稱Deep Learning and Medical Applications年度引用
書目名稱Deep Learning and Medical Applications年度引用學(xué)科排名
書目名稱Deep Learning and Medical Applications讀者反饋
書目名稱Deep Learning and Medical Applications讀者反饋學(xué)科排名
作者: 大方不好 時間: 2025-3-21 20:51
978-981-99-1841-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: TSH582 時間: 2025-3-22 03:07 作者: 積習(xí)難改 時間: 2025-3-22 04:40
https://doi.org/10.1007/978-3-658-15386-1mation related to its size and shape. Over the last few decades, many innovative methods of performing segmentation have been proposed, and these segmentation techniques are based on the basic recipes using thresholding and edge-based detection. Segmentation and classification in medical imaging are作者: superfluous 時間: 2025-3-22 08:51
https://doi.org/10.1007/978-3-658-15386-1e number of aged people with artificial prostheses and metallic implants is swiftly increasing with the rapidly aging population. Metallic objects present in the CBCT field of view produce streaking artifacts that highly degrade the reconstructed CT images, resulting in a loss of information on the 作者: Cryptic 時間: 2025-3-22 14:09
https://doi.org/10.1007/978-3-658-15386-1at integrates 3D jaw–teeth–face data from various imaging devices such as cone-beam computerized tomography (CBCT), oral scanner, face scanner, 3D tracking devices, and others. Digital dentistry equipped with the AI-based integrated platform enables dentists to provide accurate diagnoses and treatme作者: Cryptic 時間: 2025-3-22 19:35 作者: granite 時間: 2025-3-22 21:57 作者: exacerbate 時間: 2025-3-23 01:47 作者: 淺灘 時間: 2025-3-23 06:54
Jin Keun SeoProvides an understanding of the interfaces between the model and other factors, and of clinical applications.Offers comprehensive, in-depth understanding of deep learning-based medical image‘a(chǎn)nalysis作者: 譏笑 時間: 2025-3-23 12:18 作者: 哺乳動物 時間: 2025-3-23 14:37 作者: 高調(diào) 時間: 2025-3-23 21:41
,Nonlinear Representation and?Dimensionality Reduction,e been developed to process the high-dimensional data where the intrinsic dimensions are assumed to be much lower. In the very ideal case, data can be regressed linearly and DR can be performed by principal component analysis. This chapter explains the theories, principles, and practices of DR techn作者: colostrum 時間: 2025-3-24 02:07
,Deep Learning Techniques for?Medical Image Segmentation and?Object Recognition,of the output diagnosis. Therefore, in order to safely utilize DL algorithms in the medical field, it is desirable to design the models to transparently explain the reason for making the output diagnosis rather than a black-box. For explainable DL, a systematic study is needed to rigorously analyze 作者: 責(zé)任 時間: 2025-3-24 02:31
Deep Learning for Dental Cone-Beam Computed Tomography,P) algorithm. The presence of metallic objects in an imaging subject violates the model’s assumption that the CT sinogram data is equal to the Radon transform of an image. FBP ignores the polychromatic nature of the X-ray data ., which has nonlinear dependence on the distribution of the metallic obj作者: legitimate 時間: 2025-3-24 06:30
,Artificial Intelligence for?Digital Dentistry,n essential tool for almost all processes, including virtual treatment planning and on-screen simulation of surgical or dental treatment. Noting that the dental regions of 3D CT data do not have the level of resolution to be used directly for treatment, the jaw–tooth composite model, which accuratel作者: 讓空氣進入 時間: 2025-3-24 12:09 作者: 欄桿 時間: 2025-3-24 15:55 作者: Debate 時間: 2025-3-24 23:04
https://doi.org/10.1007/978-3-658-15386-1of the output diagnosis. Therefore, in order to safely utilize DL algorithms in the medical field, it is desirable to design the models to transparently explain the reason for making the output diagnosis rather than a black-box. For explainable DL, a systematic study is needed to rigorously analyze 作者: 真繁榮 時間: 2025-3-25 00:45 作者: Gudgeon 時間: 2025-3-25 04:36
https://doi.org/10.1007/978-3-658-15386-1n essential tool for almost all processes, including virtual treatment planning and on-screen simulation of surgical or dental treatment. Noting that the dental regions of 3D CT data do not have the level of resolution to be used directly for treatment, the jaw–tooth composite model, which accuratel作者: 褪色 時間: 2025-3-25 09:44
https://doi.org/10.1007/978-3-658-15386-1uation, shadows, speckles, and so on. Medical imaging is experiencing a paradigm shift due to the remarkable and rapid advancement of deep learning technology, and ultrasound companies, including Samsung Medison, are making every effort to develop a new AI-based system for automated fetal ultrasound作者: 教義 時間: 2025-3-25 13:29 作者: 價值在貶值 時間: 2025-3-25 16:55 作者: Entrancing 時間: 2025-3-25 20:29 作者: PAGAN 時間: 2025-3-26 00:44 作者: lactic 時間: 2025-3-26 04:54
Deep Learning for Dental Cone-Beam Computed Tomography,e number of aged people with artificial prostheses and metallic implants is swiftly increasing with the rapidly aging population. Metallic objects present in the CBCT field of view produce streaking artifacts that highly degrade the reconstructed CT images, resulting in a loss of information on the 作者: 武器 時間: 2025-3-26 08:27 作者: Nostalgia 時間: 2025-3-26 16:36 作者: hereditary 時間: 2025-3-26 20:34 作者: inflate 時間: 2025-3-27 00:28
Deep Learning for Ill Posed Inverse Problems in Medical Imaging,cerns in the medical imaging domain, where underdetermined problems are motivated by the willingness to provide high-resolution medical images with as little data as possible, by optimizing data collection in terms of minimal acquisition time, cost-effectiveness, and low invasiveness. DL methods app作者: Vasodilation 時間: 2025-3-27 01:46 作者: Bph773 時間: 2025-3-27 05:22 作者: 爵士樂 時間: 2025-3-27 10:40 作者: Solace 時間: 2025-3-27 16:12
Hal Harvey,Robbie Orvis,Jeffrey Rissmanty of solutions to ill-posed inverse problems. This chapter aims to discuss some mathematical interpretations of DL-based nonlinear low-dimensional representations of expected solutions to ill-posed inverse problems.作者: DEVIL 時間: 2025-3-27 21:29
Electrical Impedance Imaging,pressed as nonlinear inverse problems involving time-harmonic Maxwell’s equations with electrical tissue properties being described by frequency-dependent conductivity and permittivity. This chapter reviews electrical tissue property imaging modalities.作者: 粗鄙的人 時間: 2025-3-27 23:01 作者: 圖畫文字 時間: 2025-3-28 03:13 作者: Cpr951 時間: 2025-3-28 06:29 作者: PANT 時間: 2025-3-28 11:40 作者: Atheroma 時間: 2025-3-28 14:55
Dierck-Ekkehard Liebscherondensiert. Um keine freien Endgruppen zu erhalten, wurde wasserfrei gearbeitet. Das Reaktionsprodukt enthielt neben den nicht umgesetzten Ausgangsverbindungen haupts?chlich Oligoamide der Struktur I. Die Bildung cyclischer Amide kann mit Sicherheit ausgeschlossen werden, da Cyclo-bis-ε-aminocaproyl作者: VOC 時間: 2025-3-28 18:51
