2013 Fourth International Workshop on Computational Intelligence in Medical Imaging (CIMI)
Author: IEEE Electrical Insulation Society Staff
Publisher:
Published: 2013-04-15
Total Pages:
ISBN-13: 9781467359184
DOWNLOAD EBOOK →Author: IEEE Electrical Insulation Society Staff
Publisher:
Published: 2013-04-15
Total Pages:
ISBN-13: 9781467359184
DOWNLOAD EBOOK →Author: IEEE Staff
Publisher:
Published: 2013-04-15
Total Pages:
ISBN-13: 9781509000050
DOWNLOAD EBOOK →Nowadays medical imaging provides major aid in many branches of medicine and enables and facilitates the capture, transmission and analysis of medical images as well as provides assistance towards medical diagnoses Medical imaging is still on the rise with new imaging modalities being added and continuous improvements of devices capabilities Recently, computational intelligence techniques have been employed in various applications in the area of medical imaging Approaches based on computational intelligence have been shown to be advantageous compared to classical approaches, in particular when classical solutions are hard or impossible to formulate and analyse The International Workshop on Computational Intelligence in Medical Imaging, held as part of the IEEE Symposium Series on Computational Intelligence 2013, is envisaged as a compilation of the latest trends and developments in the field of computational intelligence in medical imaging
Author: IEEE Electrical Insulation Society Staff
Publisher:
Published: 2013
Total Pages:
ISBN-13:
DOWNLOAD EBOOK →Author: Stefan Wesarg
Publisher: Springer Nature
Published: 2023-10-09
Total Pages: 328
ISBN-13: 3031452496
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 12th International Workshop on Clinical Image-Based Procedures, CLIP 2023, the First MICCAI Workshop on Fairness of AI in Medical Imaging, FAIMI 2023, and the Second MICCAI Workshop on the Ethical and Philosophical Issues in Medical Imaging, EPIMI 2023, held in conjunction with MICCAI 2023, in October 2023. CLIP 2023 accepted 5 full papers and 3 short papers form 8 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice. For FAIMI 2023, 19 full papers have been accepted from 20 submissions. They focus on creating awareness about potential fairness issues that can emerge in the context of machine learning. And for EPIMI 2023, 2 papers have been accepted from 5 submissions. They investigate questions that underlie medical imaging research at the most fundamental level.
Author: Kensaku Mori
Publisher: Springer
Published: 2013-09-20
Total Pages: 708
ISBN-13: 3642407609
DOWNLOAD EBOOK →The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 81 papers included in the third volume have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing; imaging, reconstruction, and enhancement; segmentation; physiological modeling, simulation, and planning; intraoperative guidance and robotics; microscope, optical imaging, and histology; diffusion MRI; brain segmentation and atlases; and functional MRI and neuroscience applications.
Author: Guorong Wu
Publisher: Springer
Published: 2013-08-21
Total Pages: 262
ISBN-13: 9783319022666
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
Author: Kensaku Mori
Publisher: Springer
Published: 2013-09-20
Total Pages: 836
ISBN-13: 3642408117
DOWNLOAD EBOOK →The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 95 papers included in the first volume have been organized in the following topical sections: physiological modeling and computer-assisted intervention; imaging, reconstruction, and enhancement; registration; machine learning, statistical modeling, and atlases; computer-aided diagnosis and imaging biomarkers; intraoperative guidance and robotics; microscope, optical imaging, and histology; cardiology, vasculatures and tubular structures; brain imaging and basic techniques; diffusion MRI; and brain segmentation and atlases.
Author: G. Schaefer
Publisher: CRC Press
Published: 2009-03-24
Total Pages: 512
ISBN-13: 1420060619
DOWNLOAD EBOOK →CI Techniques & Algorithms for a Variety of Medical Imaging SituationsDocuments recent advances and stimulates further researchA compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical
Author: K.C. Santosh
Publisher: CRC Press
Published: 2019-08-20
Total Pages: 200
ISBN-13: 0429639325
DOWNLOAD EBOOK →The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.