• Journal of Digital Convergence
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• v.15 no.2
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• pp.173-181
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• 2017

In this paper, we have studied tracking as a training stage of considering the position and the scale of a person given its previous position, scale, as well as next and forward image fraction. Unlike other learning methods, CNN is thereby learning combines both time and spatial features from the image for the two consecutive frames. We introduce multiple path ways in CNN to better fuse local and global information. A creative shift-variant CNN architecture is designed so as to alleviate the drift problem when the distracting objects are similar to the target in cluttered environment. Furthermore, we employ CNNs to estimate the scale through the accurate localization of some key points. These techniques are object-independent so that the proposed method can be applied to track other types of object. The capability of the tracker of handling complex situations is demonstrated in many testing sequences. The accuracy of the SVM classifier using the features learnt by the CNN is equivalent to the accuracy of the CNN. This fact confirms the importance of automatically optimized features. However, the computation time for the classification of a person using the convolutional neural network classifier is less than approximately 1/40 of the SVM computation time, regardless of the type of the used features.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.455-468
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• 1998

For the objective interpretation of cerebral metabolic patterns in epilepsy patients, we developed computer-aided classifier using artificial neural network. We studied interictal brain FDG PET scans of 257 epilepsy patients who were diagnosed as normal(n=64), L TLE (n=112), or R TLE (n=81) by visual interpretation. Automatically segmented volume of interest (VOI) was used to reliably extract the features representing patterns of cerebral metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

• Applied Microscopy
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• v.24 no.4
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• pp.61-77
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• 1994

The calcium-binding proteins (CaBP), parvalbumin (PV) and calbindin-D 28K (calbindin) are particularly abundant and specific in their distribution, and present in different subsets of neurons in many brain regions. Although their physiological roles in the neurons have not been elucidated, they are valuable markers of neuronal subpopulations for anatomical and developmental studies. This study is designed to characterize dorsal lateral geniculate nucleus (dLGN) neurons and axon terminals in terms of differential expression of immunoreactivity (IR) for two well-known CaBPs, PV and calbindin. The experiments were carried out on 6 adult monkeys. Monkeys were perfused under deep Nembutal anesthesia with 2% paraformaldehyde and 0.2% glutaraldehyde in 0.1M phosphate buffer. After removal, the brains were postfixed for 6-8 hr in 2% paraformaldehyde at $4^{\circ}C$ and infiltrated with 30% sucrose at $4^{\circ}C$. Thereafter, they were frozen in dry ice. Serial sections of the thalamus, at $20{\mu}m$, were made in the frontal plane with a sliding microtome. The sections were stained for PV and calbindin with indirect immunocytochemical methods. For electron microscopy, after infiltration with 30% sucrose the blocks of thalamus were serially sectioned at $50{\mu}m$ with a Vibratome in the coronal plane and stained immediately by indirect ABC methods without Triton X-100 in incubation medium. Stained sections were postfixed in 0.2% osmium tetroxide, dehydrated and flat-embedded in Spurr resin. The block was then trimmed to contain only a selected lamina or interlaminar space. The dLGN proper showed strong PV IR in fibers in all laminae and interlaminar zones. Particularly dense staining was noted in layers 1 and 2 that contain many stained fibers from optic tract. Neuronal cell body stained with PV was concentrated only in the laminae. In these laminae staining was moderate in cell bodies of all large and medium-sized neurons, and was strong in cell bodies of some small neurons together with their processes. Calbindin IR was marked in the neuronal cell body and neuropil in the S layers and interlaminar zones whereas moderate in the neuropil throughout the nucleus. Regional difference in distribution of PV and calbindin IR cell is distinct; the former is only in the laminae and the latter in both the S layer and interlaminar space. The CaBP-IR elements were confined to about $10{\mu}m$ in depth of Vibratome section. The IR product for CaBP was mainly associated with synaptic vesicle, pre- and post-synaptic membrane, and outer mitochondrial membrane and along microtubule. PV-IR was noted in various neuronal elements such as neuronal soma, dendrite, RLP, F, PSD and some myelinated or unmyelinated axons, and was not seen in the RSD and glial cells. Only a few neuronal components in dLGN was IR for calbindin and its reaction product was less dense than that of PV, and scattered throughout cytoplasm of soma of some relay neurons, and was also persent in some dendrite, myelinated axons and RLP. The RSD, F, PSD and glial elements were always non-IR for calbindin. Calbindin labelled RLP were presynaptic to unlabeled dendrite or dendritic spine and PSD. Calbindin-labeled dendrite of various sizes were always postsynaptic to unlabeled RSD, RLP or F. From this study it is suggested that dLGN cells of different functional systems and their differential projection to the visual cortex can be distinguished by differential expression of PV and calbindin.

• Progress in Medical Physics
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• v.14 no.2
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• pp.90-98
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• 2003

Purpose : A new virtual simulation technique for craniospinal irradiation (CSI) that uses a CT-simulator was developed to improve the accuracy of field and shielding placement as well as patient positioning. Materials and Methods : A CT simulator (CT-SIM) and a 3-D conformal radiation treatment planning system (3D-CRT) were used to develop CSI. The head and neck were immobilized with a thermoplastic mask while the rest of the body was immobilized with a Vac-Loc. A volumetric image was then obtained with the CT simulator. In order to improve the reproducibility of the setup, datum lines and points were marked on the head and body. Virtual fluoroscopy was performed with the removal of visual obstacles, such as the treatment table or immobilization devices. After virtual simulation, the treatment isocenters of each field were marked on the body and on the immobilization devices at the conventional simulation room. Each treatment fields was confirmed by comparing the fluoroscopy images with the digitally reconstructed radiography (DRR) and digitally composited radiography (DCR) images from virtual simulation. Port verification films from the first treatment were also compared with the DRR/DCR images for geometric verification. Results : We successfully performed virtual simulations on 11 CSI patients by CT-SIM. It took less than 20 minutes to affix the immobilization devices and to obtain the volumetric images of the entire body. In the absence of the patient, virtual simulation of all fields took 20 min. The DRRs were in agreement with simulation films to within 5 mm. This not only reducee inconveniences to the patients, but also eliminated position-shift variables attendant during the long conventional simulation process. In addition, by obtaining CT volumetric image, critical organs, such as the eyes and the spinal cord, were better defined, and the accuracy of the port designs and shielding was improved. Differences between the DRRs and the portal films were less than 3 m in the vertebral contour. Conclusion : Our analysis showed that CT simulation of craniospinal fields was accurate. In addition, CT simulation reduced the duration of the patient's immobility. During the planning process. This technique can improve accuracy in field placement and shielding by using three-dimensional CT-aided localization of critical and target structures. Overall, it has improved staff efficiency and resource utilization by standard protocol for craniospinal irradiation.