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"Conveys the essential knowledge needed to understand the clinical application of imaging technologies. Suitable for radiology residents and students, this title covers various subspecialty areas and imaging modalities as utilized in neuroradiology, chest, breast, abdominal, musculoskeletal imaging, ultrasound, and nuclear radiology "

"Visual Computing for medicine, second edition, offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment. The book includes algorithms, applications, and ideas on achieving reliability of results and clinical evaluation of the techniques covered. Preim and botha illustrate visualization techniques from research, but also cover the information required to solve practical clinical problems. They base the book on several years of combined teaching and research experience. This new edition includes six new chapters on treatment planning, guidance and training; an updated appendix on software support for visual computing for medicine; and a new global structure that better classifies and explains the major lines of work in the field."

"Il successo del trattamento chirurgico implantare è strettamente correlato a un’adeguata pianificazione dell’intervento e a una rigorosa valutazione preoperatoria. L’impiego di software di ricostruzione delle immagini dedicati alla diagnostica dentale, del tipo Dentascan, permette di ottenere ricostruzioni cross-section e simil-panoramiche (panorex) che misurano la quantità di tessuto osseo disponibile e definiscono accuratamente le strutture anatomiche contigue o la presenza di eventuali patologie associate. Questo manuale, dal taglio pratico e sintetico, affronta le principali questioni di ordine tecnico e metodologico relative allo studio TC mirato delle arcate dentarie e alla descrizione dell’anatomia e dei punti critici. Particolare rilievo è attribuito alle problematiche relative alla valutazione pre-implantologica, ai risultati e alle complicanze del trattamento, con cenni anche ad alcune indicazioni extra-implantari"

"Most books discuss general and broad topics regarding molecular imagings. however, Ultrasmall lanthanide oxide nanoparticles for biomedical imaging and therapy, will mainly focus on lanthanide oxide nanoparticles for molecular imaging and therapeutics. multi-modal imaging capabilities will discussed, along with up-converting FI by using lanthanide oxide nanoparticles. the synthesis will cover polyol synthesis of lanthanide oxide nanoparticles, surface coatings with biocompatible and hydrophilic ligands will be discussed and tem images and dynamic light scattering (dls) patterns will be provided. various techniques which are generally used in analyzing the synthesized surface coated nanoparticles will be explored and this section will also cover ft , ir analysis, xrd analysis, squid analysis, cytotoxicity measurements and proton relaxivity measurements. in vivo mr images, ct images, fluorescence images will be provided and therapeutic application of gadolinium oxide nanoparticles will be discussed. finally, future perpectives will be discussed. that is, present status and future works needed for clinical applications of lanthanide oxide nanoparticles to molecular imagings will be discussed."

"This volume presents the proceedings of the International Conference on Biomedical and Health Informatics (ICBHI). The conference was a new special topic conference and a common initiative by the International Federation of Medical and Biological Engineering (IFMBE) and IEEE Engineering in Medicine and Biology Society (IEEE- EMBS). BHI2015 was held in Haikou, China, 8-10 October 2015. The main theme of the BHI2015 is The Convergence: Integrating Information and Communication Technologies with Biomedicine for Global Health.The ICBHI2015 proceedings examine enabling technologies of sensors, devices and systems that optimize the acquisition, transmission, processing, storage, retrieval, use of biomedical and health information as well as to report novel clinical applications of health information systems and the deployment of m-Health, e-Health, u-Health, p-Health and Telemedicine. "

"Penyakit mata berat yang telat tertangani seperti katarak, glaukoma, serta retinopati diabetik merupakan salah satu penyebab utama gangguan penglihatan dan kebutaan. Pencegahan dapat dilakukan dengan melakukan pendektesian dini melalui citra fundus. Untuk mengatasi minimnya dokter mata dan persebarannya yang masih belum merata, dilakukan pendektesian penyakit mata secara otomatis melalui gambar mata dengan pendekatan deep learning. Dalam penelitian ini, digunakan metode Transfer Learning U-Net dengan VGG16 sebagai pretrained model (V-Unet) yang telah dilatih pada online database, ImageNet. Data yang digunakan dalam penelitian ini merupakan data citra fundus yang diperoleh dari platform Kaggle. Preprocessing data pada citra fundus yang dilakukan untuk meningkatkan kinerja model adalah centered crop, resize, dan rescale. Fungsi optimasi Adam digunakan untuk meminimalkan fungsi loss ketika melatih model. Pada penelitian ini, dilakukan pemisahan data training, validasi, testing dengan 3 rasio berbeda, yaitu kasus I dengan rasio 60:20:20, kasus II dengan rasio 70:20:10, dan kasus III dengan rasio 80:10:10. Hasil penelitian ini menunjukkan bahwa V-Unet memiliki kinerja paling baik pada kasus II berdasarkan skor AUC dan running time dengan nilai rata-rata skor AUC 0,8622 dan rata-rata running time 3,7079 detik sedangkan berdasarkan nilai akurasinya V-Unet memiliki kinerja paling baik pada kasus III dengan rata-rata nilai akurasi sebesar 66,34%.

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Untreated severe eye diseases such as cataracts, glaucoma, and diabetic retinopathy is one of the main causes of visual impairment and blindness. Prevention can be done by doing early detection through fundus images. To overcome the lack of ophthalmologists and their uneven distribution, an automatic detection of eye diseases is carried out through eye images using a deep learning approach. In this study, Transfer Learning U-Net method was used with VGG16 as a pre-trained model (V-Unet) which had been trained on the online database, ImageNet . The data used in this study is fundus image data that obtained from the Kaggle platform. Preprocessing data on the fundus image that is carried out to improve model performance is centered crop, resize, and rescale. Adam's optimization function used to minimize the loss function when training the model. In this study, the training, validation, testing data was separated with 3 different ratios, namely case I with a ratio of 60:20:20, case II with a ratio of 70:20:10, and case III with a ratio of 80:10:10. The results of this study indicate that V-Unet has the best performance in case II based on the AUC score and running time with an average AUC score of 0.8622 and an average running time of 3.7079 seconds while based on accuracy value the best case is case III with an average accuracy value of 66.34%."

"This book constitutes the refereed proceedings of the International Workshop on Mesh Processing in Medical Image Analysis, MeshMed 2012, held in Nice, France, in October 2012 in conjunction with MICCAI 2012, the 15th International Conference on Medical Image Computing and Computer Assisted Intervention. The book includes 16 submissions, 8 were selected for presentation along with the 3 plenary talks representative of the meshing, and 8 were selected for poster presentations. The papers cover a broad range of topics, including statistical shape analysis and atlas construction, novel meshing approaches, soft tissue simulation, quad dominant meshing and mesh based shape descriptors. The described techniques were applied to a variety of medical data including cortical bones, ear canals, cerebral aneurysms and vascular structures."