標(biāo)題: Titlebook: Biomedical Imaging; Advances in Artifici Ankur Gogoi,Nirmal Mazumder Book 2024 The Editor(s) (if applicable) and The Author(s), under exclu [打印本頁(yè)] 作者: 警察在苦笑 時(shí)間: 2025-3-21 17:31
書目名稱Biomedical Imaging影響因子(影響力)
書目名稱Biomedical Imaging影響因子(影響力)學(xué)科排名
書目名稱Biomedical Imaging網(wǎng)絡(luò)公開度
書目名稱Biomedical Imaging網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Biomedical Imaging被引頻次
書目名稱Biomedical Imaging被引頻次學(xué)科排名
書目名稱Biomedical Imaging年度引用
書目名稱Biomedical Imaging年度引用學(xué)科排名
書目名稱Biomedical Imaging讀者反饋
書目名稱Biomedical Imaging讀者反饋學(xué)科排名
作者: Harbor 時(shí)間: 2025-3-21 21:26 作者: 貴族 時(shí)間: 2025-3-22 04:13 作者: CUR 時(shí)間: 2025-3-22 07:08 作者: FADE 時(shí)間: 2025-3-22 11:29 作者: 淺灘 時(shí)間: 2025-3-22 14:06 作者: inflate 時(shí)間: 2025-3-22 20:26 作者: 多產(chǎn)魚 時(shí)間: 2025-3-22 21:45 作者: 左右連貫 時(shí)間: 2025-3-23 03:22
U-Net: A Versatile Deep Learning Architecture for Multi-Disease Detection,aging modalities. The chapter highlights variants of U-Nets and presents various data augmentation techniques to improve the performance. The chapter covers the segmentation of brain tumors, lung nodules, and liver lesions.作者: 猛烈責(zé)罵 時(shí)間: 2025-3-23 07:28
Deep Learning Integrated Multiphoton Microscopy,es. DL is assisting us in moving toward data-driven instrument designs that combine microscopy and computing techniques. This article gives an overview of recent work that has used ML techniques to various?types of advanced?microscopy and sensing systems and their biomedical applications.作者: jocular 時(shí)間: 2025-3-23 13:02
Artificial Intelligence in Diagnostic Medical Image Processing for Advanced Healthcare Applicationscal impedance tomography (EIT), positron emission tomography (PET), and (optical) microscopic imaging, have significantly propelled healthcare by elucidating intricate details of human tissues and organs. Despite these achievements, challenges persist in terms of image acquisition, processing, big m作者: circuit 時(shí)間: 2025-3-23 16:45
From Pixels to Predictions: Exploring the Role of Artificial Intelligence in Radiology,cial intelligence (AI) is quickly making headway in the field of radiology. AI, when used effectively, can be beneficial in the education of future doctors. Technological developments frequently cause changes in the field of radiology. Therefore, a new storage device, image distribution system, or s作者: 商店街 時(shí)間: 2025-3-23 18:18 作者: CRUDE 時(shí)間: 2025-3-24 00:16
Tracing Historical Connections: The Evolutionary Ties of Artificial Intelligence, Confocal Microscoion, highlighting the intersection of these disciplines. As a luminary in the field of AI, Minsky‘s foundational work at the Massachusetts Institute of Technology‘s Artificial Intelligence Laboratory set the stage for neural network research and computational theories of mind. Simultaneously, Minsky作者: wall-stress 時(shí)間: 2025-3-24 05:16 作者: 削減 時(shí)間: 2025-3-24 10:25 作者: defibrillator 時(shí)間: 2025-3-24 13:57 作者: 偽證 時(shí)間: 2025-3-24 17:12
Two Photon Fluorescence Integrated Machine Learning for Data Analysis and Interpretation,tists to tackle complex biological questions with unprecedented precision. This chapter explores the transformative potential of this integrated approach across multiple domains, particularly in cancer biology, stem cell research, and brain science. By harnessing the high-resolution imaging capabili作者: Amnesty 時(shí)間: 2025-3-24 19:24 作者: 接觸 時(shí)間: 2025-3-25 02:56 作者: Assignment 時(shí)間: 2025-3-25 03:53
Deep Learning Integrated Multiphoton Microscopy,eated transformative opportunities for image reconstruction and enhancement in optical microscopy. DL is being used to solve various inverse problems based on microscopy image data, from image transformations between microscopic imaging systems to adding new capabilities to existing imaging techniqu作者: 金盤是高原 時(shí)間: 2025-3-25 11:06 作者: 乞丐 時(shí)間: 2025-3-25 14:31
,Memristor-Based Neuromorphic Computing and Artificial Neural Networks for Computer Vison and AI—App of energy consumption. The objective is to emulate the computational functions of the human brain, with special attention to attaining high compactness and energy efficiency. On the way to achieving this goal, there are a number of formidable obstacles. Because the biological brain uses extremely l作者: AMITY 時(shí)間: 2025-3-25 19:33 作者: jettison 時(shí)間: 2025-3-25 22:30
https://doi.org/10.1007/978-981-97-5345-1Medical Image Processing; Biophotonics; Cancer Diagnosis; Diffuse Optical Imaging; Nonlinear Optical Mic作者: bypass 時(shí)間: 2025-3-26 03:10 作者: 制定法律 時(shí)間: 2025-3-26 07:01
Ronald S. Valle,Rolf Eckartsbergcal impedance tomography (EIT), positron emission tomography (PET), and (optical) microscopic imaging, have significantly propelled healthcare by elucidating intricate details of human tissues and organs. Despite these achievements, challenges persist in terms of image acquisition, processing, big m作者: 真實(shí)的你 時(shí)間: 2025-3-26 09:58 作者: helper-T-cells 時(shí)間: 2025-3-26 13:57
https://doi.org/10.1057/9780230590687urgical intervention. Various types of biomedical imaging techniques help in the diagnosis of various diseases. In the present day, artificial intelligence has been implemented to improve the healthcare sector. Many researchers have various opinions on the applications of Artificial Intelligence and作者: Dedication 時(shí)間: 2025-3-26 20:34
Conclusion: Metaphors We Globalize Byion, highlighting the intersection of these disciplines. As a luminary in the field of AI, Minsky‘s foundational work at the Massachusetts Institute of Technology‘s Artificial Intelligence Laboratory set the stage for neural network research and computational theories of mind. Simultaneously, Minsky作者: NICE 時(shí)間: 2025-3-27 00:48
Conclusion: Metaphors We Globalize Byorphology. Coherent anti-Stokes Raman scattering (CARS), Stimulated Raman scattering (SRS) are used as a tool to observe structural and chemical changes at cellular resolution. There are?many methods used to detect cell death generally takes?time and materials. Spectroscopic and microscopic analyses作者: Cognizance 時(shí)間: 2025-3-27 01:15
Conclusion: Metaphors We Globalize Byiven technologies have revolutionized healthcare, particularly in the realm of medical imaging analysis. In the context of oral cavity cancer detection, AI systems leverage advanced algorithms to analyze digital images captured using smartphones or digital cameras. These images serve as visual recor作者: 云狀 時(shí)間: 2025-3-27 05:47 作者: MORPH 時(shí)間: 2025-3-27 13:25
How to Make Our Ideas Clear With Metaphorstists to tackle complex biological questions with unprecedented precision. This chapter explores the transformative potential of this integrated approach across multiple domains, particularly in cancer biology, stem cell research, and brain science. By harnessing the high-resolution imaging capabili作者: Charitable 時(shí)間: 2025-3-27 16:29
How to Make Our Ideas Clear With Metaphorsen going through since our evolution. The biomedical field is continuously upgrading and making required changes that can decrease the incidence and mortality rate associated with such diseases. One persistent problem still needs to overcome which is the diagnosis of these diseases at its early stag作者: dandruff 時(shí)間: 2025-3-27 19:47
Of Mind, Metaphysics and Other Mattersifically, in this chapter, a deep analysis of existing Convolution Neural Network (CNN) models (for Covid-19 detection), is presented from the perspective of data imbalance. Covid-19 disease had a disastrous effect on human life, since 2020. One of the effective ways of diagnosing Covid-19 disease i作者: RENIN 時(shí)間: 2025-3-28 00:04 作者: 兩棲動(dòng)物 時(shí)間: 2025-3-28 06:04
Artificial Intelligence and the Natural Bodys led to the penetration of Artificial Intelligence, which improved the objectivity of analysis. The emergence of Convolution Neural Networks (CNN) allowed semantic segmentation of medical images, allowing pixel-level understanding. U-Net is a CNN, which is among the most robust architectures resear作者: FADE 時(shí)間: 2025-3-28 08:53 作者: MAPLE 時(shí)間: 2025-3-28 13:30
https://doi.org/10.1007/978-94-010-0088-8red the creation of a ground-breaking imaging method,?he called “computerized axial transverse scanning.” This technique’s core idea was very straightforward: a pencil-sized x-ray beam was used to analyze a thin cross-section of the head, known as the tomographic slice, at various angles. The scinti作者: slipped-disk 時(shí)間: 2025-3-28 16:21
Biomedical Imaging978-981-97-5345-1Series ISSN 1618-7210 Series E-ISSN 2197-5647 作者: SPURN 時(shí)間: 2025-3-28 19:28 作者: 強(qiáng)制令 時(shí)間: 2025-3-29 00:25 作者: BIPED 時(shí)間: 2025-3-29 04:24 作者: refraction 時(shí)間: 2025-3-29 07:33
Conclusion: Metaphors We Globalize Byning that machines using deep learning-based software will soon take over their field. Corroborating evidence suggested that several algorithms could perform numerous tasks far more effectively than the typical radiologist. As previously said, by reason of recent events, radiology trainees feel vuln作者: 大范圍流行 時(shí)間: 2025-3-29 12:49 作者: 新陳代謝 時(shí)間: 2025-3-29 18:08
Conclusion: Metaphors We Globalize Byt to pushing the boundaries of scientific exploration. His impact on AI and CM was not confined to theoretical contributions but extended to practical innovations that continue to shape these fields today. Through a multidisciplinary lens, the chapter aims to underscore Minsky’s trailblazing contrib作者: peak-flow 時(shí)間: 2025-3-29 23:42
Conclusion: Metaphors We Globalize By the sample size. Despite the advantages that spectroscopy techniques offer, the complexity of the spectroscopic peaks is a major drawback. This gives rise to the need to develop automated algorithms for analysing high throughput spectroscopic and microscopic value with great efficiency and accuracy作者: 易于出錯(cuò) 時(shí)間: 2025-3-30 01:12
Conclusion: Metaphors We Globalize ByCNNs), deep learning models, and attention-based mechanisms. It also addresses challenges and limitations, such as ensuring image quality, addressing algorithmic biases, and the importance of the human–computer interface. Additionally, ethical considerations related to data privacy, informed consent作者: 很像弓] 時(shí)間: 2025-3-30 04:34
How to Make Our Ideas Clear With Metaphors and treatment. Similarly, in stem cell research, the combination of two-photon microscopy and ML enables quantitative analysis of stem cell dynamics, lineage commitment, and differentiation trajectories in complex 3D microenvironments, facilitating advancements in regenerative medicine and drug dis作者: 清楚 時(shí)間: 2025-3-30 11:18
How to Make Our Ideas Clear With Metaphorssease diagnostic tool by researchers and practitioners in recent years. Raman spectroscopy, a vibrational spectroscopic tool is a label-free, reliably non-invasive, rapid, easy-to-use, efficient, and sensitive to biomolecular changes in the human body. This book chapter is a dedicated explanation of作者: 燦爛 時(shí)間: 2025-3-30 15:05 作者: 大炮 時(shí)間: 2025-3-30 18:26
https://doi.org/10.1007/978-94-010-0088-8 be known as computerized axial tomography (CAT), which now is popularly called computed tomography (CT). Like many great discoveries, CT was the end product of years of work put on by various investigators. Throughout the years, CT has undergone multiple improvements. In this chapter, we will deal 作者: 一夫一妻制 時(shí)間: 2025-3-30 22:55
1618-7210 d complicated datasets and providing clear insight into the potential abnormalities with excellent accuracy, sensitivity, and specificity. The hallmark of this book will be the contributions from international 978-981-97-5347-5978-981-97-5345-1Series ISSN 1618-7210 Series E-ISSN 2197-5647 作者: Cervical-Spine 時(shí)間: 2025-3-31 01:19
Artificial Intelligence in Diagnostic Medical Image Processing for Advanced Healthcare Applicationscal imaging. We study the workflow of AI in tasks such as image reconstruction, analysis, interpretation, segmentation, and enhancement. Additionally, we explore its role in computer-aided diagnosis (CAD), treatment planning, patient group classification, and predicting and reducing radiotherapy dos作者: intention 時(shí)間: 2025-3-31 06:39
From Pixels to Predictions: Exploring the Role of Artificial Intelligence in Radiology,ning that machines using deep learning-based software will soon take over their field. Corroborating evidence suggested that several algorithms could perform numerous tasks far more effectively than the typical radiologist. As previously said, by reason of recent events, radiology trainees feel vuln作者: 使增至最大 時(shí)間: 2025-3-31 10:55
Challenges in Accurately Using Artificial Intelligence and Machine Learning in Biomedical Imaging,biomedical imaging. To understand the numerous challenges linked to the application of AI/ML in biomedical imaging. This will assist researchers in maintaining awareness of the challenges encountered when utilizing AI/ML in the context of biomedical imaging.作者: 無(wú)表情 時(shí)間: 2025-3-31 16:48 作者: SNEER 時(shí)間: 2025-3-31 17:53
