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The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2019, the 26th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.
The conference covers all aspects of the technology associated with ultrasound generation and detection and their applications.
This conference is the annual premier meeting on the use of instrumentation in the Nuclear and Medical fields. The meeting has a very long history of providing an exciting venue for scientists to present their latest advances, exchange ideas, renew existing collaboration and form new ones. The NSS portion of the conference is an ideal forum for scientists and engineers in the field of Nuclear Science, radiation instrumentation, software engineering and data acquisition. The MIC is one of the most informative venues on the state-of-the art use of physics, engineering, and mathematics in Nuclear Medicine and related imaging modalities, such as CT and increasingly so MRI, through the development of hybrid devices
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2001
We show that dyadic scales may not be sufficient for the detection of masses in mammograms: a lesion may be too blurred on one scale, and then too fragmented at the next. In this paper, we report on the preliminary evidence of our study using a continuous wavelet transform in two dimensions with arbitrary positioning of a wavelet's center frequency ...
Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), 2003
The first pathologic alterations of the retina are seen in the vessel network. These modifications affect very differently arteries and veins, and the appearance and entity of the modification differ as the retinopathy becomes milder or more severe. In order to develop an automatic procedure for the diagnosis and grading of retinopathy, it is necessary to be able to discriminate ...
2006 IEEE Nuclear Science Symposium Conference Record, 2006
We use receiver operating characteristic (ROC) analysis of a location-known- exactly (LKE) lesion detection task to compare the image quality of SPECT reconstruction with and without various combinations of attenuation correction (AC), scatter correction (SC) and resolution compensation (RC). Hybrid images were generated from Tc-99m labelled NeoTect clinical backgrounds into which Monte Carlo simulated solitary pulmonary nodule (SPN) lung lesions ...
Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000
The initial characterization results of detector modules allow one to foresee that the single photon compact ring tomograph for high resolution breast imaging can be a promising technique as well as having the exciting potential to make a real contribution to the field of breast imaging. This project is a part of larger research project including simultaneous transmission and emission ...
Proceedings Technology Requirements for Biomedical Imaging, 1991
We show that dyadic scales may not be sufficient for the detection of masses in mammograms: a lesion may be too blurred on one scale, and then too fragmented at the next. In this paper, we report on the preliminary evidence of our study using a continuous wavelet transform in two dimensions with arbitrary positioning of a wavelet's center frequency channel tuned to the mass detection problem. Our goal is to detect masses in dense mammograms whose diameter is smaller than 1 cm. The aim is to be able to find the scale where the mass is best represented in terms of analysis.
The first pathologic alterations of the retina are seen in the vessel network. These modifications affect very differently arteries and veins, and the appearance and entity of the modification differ as the retinopathy becomes milder or more severe. In order to develop an automatic procedure for the diagnosis and grading of retinopathy, it is necessary to be able to discriminate arteries from veins. The problem is complicated by the similarity in the descriptive features of these two structures and by the contrast and luminosity variability of the retina. We developed a new algorithm for classifying the vessels, which exploits the peculiarities of retinal images. By applying a divide et impera approach that partitioned a concentric zone around the optic disc into quadrants, we were able to perform a more robust local classification analysis. The results obtained by the proposed technique were compared with those provided by a manual classification on a validation set of 443 vessels and reached an overall classification error of 12%, which reduces to 7% if only the diagnostically important retinal vessels are considered.
We use receiver operating characteristic (ROC) analysis of a location-known- exactly (LKE) lesion detection task to compare the image quality of SPECT reconstruction with and without various combinations of attenuation correction (AC), scatter correction (SC) and resolution compensation (RC). Hybrid images were generated from Tc-99m labelled NeoTect clinical backgrounds into which Monte Carlo simulated solitary pulmonary nodule (SPN) lung lesions were added, then reconstructed using several strategies. Results from a human-observer study show that attenuation correction degrades SPN detection, while resolution correction improves SPN detection, even when the lesion location is known. This agrees with the results of a previous localization-response operating characteristic (LROC) study using the same images, indicating that location uncertainty is not the sole source of the changes in detection accuracy.
The initial characterization results of detector modules allow one to foresee that the single photon compact ring tomograph for high resolution breast imaging can be a promising technique as well as having the exciting potential to make a real contribution to the field of breast imaging. This project is a part of larger research project including simultaneous transmission and emission tomography. Finally, this tomographic system can have a relevance which extends beyond the field of breast imaging to other areas of nuclear medicine imaging as well as the more general scope of nuclear radiation detection.
This research presents the development of an expert system for diagnosis plant diseases in Barracuda mango (Nam-Dok Mai) which is one of a major export agricultural yield of Thailand. However, Thailand is in a tropical country and the climate causes the variation of plant diseases that affect to the growth of mango trees. Many type of agriculture yield are decreased due to an agriculturist are lacking of knowledge on how to classify type of plant disease correctly. Moreover, there is no suggestion system for a decision- making in choosing a suitable way to prevent or treat the disease that occur in their farm. This causes a lot of error in their infected plant treatments. Therefore, this system has been developed for help an agriculturist to diagnose the infected plant and to solve the problem immediately. The agriculturist should have the application which work in process of specific plant disease diagnosis as an expert human work. The plant diagnosis application applies a knowledge base system in form of rule-based model obtained by data mining technique. This paper present rule-based model with leaf image dataset. Experimental results performed that the rule-based model with 129 leaf images which collected from mango field area under supervision of product quality and standardization, Maejo University and 3 answer of class label (Anthracnose, Algal Spot, normal) has 89.92% of accuracy. From the experimental result indicated that the rules-based model can be applied to the plant diagnosis application.
The paper discusses the real-time realization of EMG signature identification for posture mapping of the upper trunk of a paraplegic as is required for controlling electrical stimulation of his/her lower limb nerves to facilitate walker-supported walking . The above method has been applied by the authors to 4 complete upper motorneuron paraplegics, with spinal cord lesions at levels T5/6 to T11/12. The purpose of the above approach is to provide naturally-controlled walking capabilities to such paraplegics, rather than using hand switches which are unnatural and, diverting the patient's concentration from his above-lesion posture (see Figure 1 and 2). For adequate control of the stimulating channel, complete posture mapping, i.e., signature identifications and control decisions, must be made in less than 0.3 seconds, else, smooth walking is hampered which in turn affects the patient's balance.
The authors consider an application of tissue characterization techniques to images obtained from intravascular ultrasound. Three methods are considered, frequency tracking based on advanced spectral estimators, tissue characterization by edge detection, and characterization by textural analysis. A computer-based imaging system was developed that uses a multi-element catheter-mounted ultrasound probe. The system is capable of reconstructing three-dimensional models of arterial structures, which may be manipulated by computer software. The 3-D imaging capability allows a much more detailed analysis of complex stenoses and arterial lesions. An example of the results of this procedure is illustrated.<<ETX>>
The differential diagnosis of focal liver lesions (FLL) frequently presents a dilemma, as FLL cannot be reliably characterized with conventional ultrasound. Recently, ultrasound contrast agents (UCA) and contrast-specific imaging methods have substantially improved the characterization of FLL. This was made possible by the known differences in dynamic vascular patterns (DVP) between healthy parenchyma and various FLL types, revealed by UCA. The purpose of this work was to develop a new method, called DVP processing, which provides a DVP- enhanced imaging mode of FLL using contrast ultrasound; this mode allows an improved differentiation of benign from malignant lesions. DVP processing consists in generating a sequence of images, where hyper-echoic and hypo- echoic pixels, compared to reference levels taken in healthy parenchyma, are coded over time in warm and cold colors, respectively. For example, a benign lesion remains hyper-echoic over time, while a malignant lesion is hyper- echoic in the arterial phase and turns into hypo-echoic in the portal phase. This method was implemented as an image-processing software program, which was the object of clinical evaluation. Sequences of 111 FLL were acquired with real-time low-MI contrast- specific ultrasound after a 2.5-mL bolus injection of SonoVuetrade, and subsequently analyzed off-fine with DVP processing. The sensitivity and specificity achieved by two clinical observers in this way were 92%, and 86%, respectively. These results reflect a significant improvement over accuracy scores achieved with contrast-enhanced ultrasound alone, having resulted in 93% and 82% in sensitivity and specificity, respectively.
Automated Breast Ultrasound (ABUS) is highly effective as breast cancer screening adjunct technology. Automation can greatly enhance the efficiency of the clinician sifting through the quantum of data in ABUS volumes to spot lesions. We have implemented a fully automatic generic algorithm pipeline for detection and characterization of lesions on such 3D volumes. We compare a wide range of features for region description on their effectiveness at the dual goals of lesion detection and characterization. On multiple feature images, we compute region descriptors at lesion candidate locations obviating the need for explicit lesion segmentation. We use Random Forests classifier to evaluate candidate region descriptors for lesion detection. Further, we categorize true lesions as Malignant or other masses (e.g. Cysts). Over a database of 145 volumes, with 36 biopsy verified lesions, we achieved Area Under the Curve (AUC) values of 92.6% for lesion detection and 89% for lesion characterization.
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