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Showing 1 to 12 of 22 entries
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LIVER WHOLE SLIDE IMAGE ANALYSIS FOR 3D VESSEL RECONSTRUCTION.

Proceedings. IEEE International Symposium on Biomedical Imaging

Liang Y, Wang F, Treanor D, Magee D, Teodoro G, Zhu Y, Kong J.
PMID: 26405504
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:182-185. doi: 10.1109/ISBI.2015.7163845.

The emergence of digital pathology has enabled numerous quantitative analyses of histopathology structures. However, most pathology image analyses are limited to two-dimensional datasets, resulting in substantial information loss and incomplete interpretation. To address this, we have developed a complete...

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Liang Y, Wang F, Treanor D, et al. LIVER WHOLE SLIDE IMAGE ANALYSIS FOR 3D VESSEL RECONSTRUCTION. Proc IEEE Int Symp Biomed Imaging. 2015;2015:182-185doi: 10.1109/ISBI.2015.7163845.
Liang, Y., Wang, F., Treanor, D., Magee, D., Teodoro, G., Zhu, Y., & Kong, J. (2015). LIVER WHOLE SLIDE IMAGE ANALYSIS FOR 3D VESSEL RECONSTRUCTION. Proceedings. IEEE International Symposium on Biomedical Imaging, 2015182-185. https://doi.org/10.1109/ISBI.2015.7163845
Liang, Yanhui, et al. "LIVER WHOLE SLIDE IMAGE ANALYSIS FOR 3D VESSEL RECONSTRUCTION." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 182-185. doi: https://doi.org/10.1109/ISBI.2015.7163845
Liang Y, Wang F, Treanor D, Magee D, Teodoro G, Zhu Y, Kong J. LIVER WHOLE SLIDE IMAGE ANALYSIS FOR 3D VESSEL RECONSTRUCTION. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:182-185. doi: 10.1109/ISBI.2015.7163845. PMID: 26405504; PMCID: PMC4578313.
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A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections.

International journal of computational biology and drug design

Liang Y, Wang F, Treanor D, Magee D, Roberts N, Teodoro G, Zhu Y, Kong J.
PMID: 27034719
Int J Comput Biol Drug Des. 2016;9(1):102-119. doi: 10.1504/IJCBDD.2016.074983.

Three-dimensional (3D) high resolution microscopic images have high potential for improving the understanding of both normal and disease processes where structural changes or spatial relationship of disease features are significant. In this paper, we develop a complete framework applicable...

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Liang Y, Wang F, Treanor D, et al. A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections. Int J Comput Biol Drug Des. 2016;9(1):102-119doi: 10.1504/IJCBDD.2016.074983.
Liang, Y., Wang, F., Treanor, D., Magee, D., Roberts, N., Teodoro, G., Zhu, Y., & Kong, J. (2016). A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections. International journal of computational biology and drug design, 9(1), 102-119. https://doi.org/10.1504/IJCBDD.2016.074983
Liang, Yanhui, et al. "A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections." International journal of computational biology and drug design vol. 9,1 (2016): 102-119. doi: https://doi.org/10.1504/IJCBDD.2016.074983
Liang Y, Wang F, Treanor D, Magee D, Roberts N, Teodoro G, Zhu Y, Kong J. A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections. Int J Comput Biol Drug Des. 2016;9(1):102-119. doi: 10.1504/IJCBDD.2016.074983. PMID: 27034719; PMCID: PMC4809644.
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Scalable 3D Spatial Queries for Analytical Pathology Imaging with MapReduce.

Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Liang Y, Vo H, Aji A, Kong J, Wang F.
PMID: 28770259
Proc ACM SIGSPATIAL Int Conf Adv Inf. 2016 Oct-Nov;2016. doi: 10.1145/2996913.2996925.

3D analytical pathology imaging examines high resolution 3D image volumes of human tissues to facilitate biomedical research and provide potential effective diagnostic assistance. Such approach - quantitative analysis of large-scale 3D pathology image volumes - generates tremendous amounts of...

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Liang Y, Vo H, Aji A, et al. Scalable 3D Spatial Queries for Analytical Pathology Imaging with MapReduce. Proc ACM SIGSPATIAL Int Conf Adv Inf. 2016;2016doi: 10.1145/2996913.2996925.
Liang, Y., Vo, H., Aji, A., Kong, J., & Wang, F. (2016). Scalable 3D Spatial Queries for Analytical Pathology Imaging with MapReduce. Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2016. https://doi.org/10.1145/2996913.2996925
Liang, Yanhui, et al. "Scalable 3D Spatial Queries for Analytical Pathology Imaging with MapReduce." Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems vol. 2016 (2016). doi: https://doi.org/10.1145/2996913.2996925
Liang Y, Vo H, Aji A, Kong J, Wang F. Scalable 3D Spatial Queries for Analytical Pathology Imaging with MapReduce. Proc ACM SIGSPATIAL Int Conf Adv Inf. 2016 Oct-Nov;2016. doi: 10.1145/2996913.2996925. PMID: 28770259; PMCID: PMC5535306.
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IDEAL: a Vector-Raster Hybrid Model for Efficient Spatial Queries over Complex Polygons.

IEEE International Conference on Mobile Data Management : MDM : [proceedings]. IEEE International Conference on Mobile Data Management

Teng D, Baig F, Sun Q, Kong J, Wang F.
PMID: 34650348
IEEE Int Conf Mob Data Manag. 2021 Jun;2021. doi: 10.1109/mdm52706.2021.00024. Epub 2021 Jul 07.

Geometric computation can be heavy duty for spatial queries, in particular for complex geometries such as polygons with many edges based on a vector-based representation. While many techniques have been provided for spatial partitioning and indexing, they are mainly...

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Teng D, Baig F, Sun Q, et al. IDEAL: a Vector-Raster Hybrid Model for Efficient Spatial Queries over Complex Polygons. IEEE Int Conf Mob Data Manag. 2021;2021doi: 10.1109/mdm52706.2021.00024.
Teng, D., Baig, F., Sun, Q., Kong, J., & Wang, F. (2021). IDEAL: a Vector-Raster Hybrid Model for Efficient Spatial Queries over Complex Polygons. IEEE International Conference on Mobile Data Management : MDM : [proceedings]. IEEE International Conference on Mobile Data Management, 2021. https://doi.org/10.1109/mdm52706.2021.00024
Teng, Dejun, et al. "IDEAL: a Vector-Raster Hybrid Model for Efficient Spatial Queries over Complex Polygons." IEEE International Conference on Mobile Data Management : MDM : [proceedings]. IEEE International Conference on Mobile Data Management vol. 2021 (2021). doi: https://doi.org/10.1109/mdm52706.2021.00024
Teng D, Baig F, Sun Q, Kong J, Wang F. IDEAL: a Vector-Raster Hybrid Model for Efficient Spatial Queries over Complex Polygons. IEEE Int Conf Mob Data Manag. 2021 Jun;2021. doi: 10.1109/mdm52706.2021.00024. Epub 2021 Jul 07. PMID: 34650348; PMCID: PMC8513718.
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AUTOMATIC BRAIN ORGAN SEGMENTATION WITH 3D FULLY CONVOLUTIONAL NEURAL NETWORK FOR RADIATION THERAPY TREATMENT PLANNING.

Proceedings. IEEE International Symposium on Biomedical Imaging

Duanmu H, Kim J, Kanakaraj P, Wang A, Joshua J, Kong J, Wang F.
PMID: 32802270
Proc IEEE Int Symp Biomed Imaging. 2020 Apr;2020:758-762. doi: 10.1109/isbi45749.2020.9098485. Epub 2020 May 22.

3D organ contouring is an essential step in radiation therapy treatment planning for organ dose estimation as well as for optimizing plans to reduce organs-at-risk doses. Manual contouring is time-consuming and its inter-clinician variability adversely affects the outcomes study....

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Duanmu H, Kim J, Kanakaraj P, et al. AUTOMATIC BRAIN ORGAN SEGMENTATION WITH 3D FULLY CONVOLUTIONAL NEURAL NETWORK FOR RADIATION THERAPY TREATMENT PLANNING. Proc IEEE Int Symp Biomed Imaging. 2020;2020:758-762doi: 10.1109/isbi45749.2020.9098485.
Duanmu, H., Kim, J., Kanakaraj, P., Wang, A., Joshua, J., Kong, J., & Wang, F. (2020). AUTOMATIC BRAIN ORGAN SEGMENTATION WITH 3D FULLY CONVOLUTIONAL NEURAL NETWORK FOR RADIATION THERAPY TREATMENT PLANNING. Proceedings. IEEE International Symposium on Biomedical Imaging, 2020758-762. https://doi.org/10.1109/isbi45749.2020.9098485
Duanmu, Hongyi, et al. "AUTOMATIC BRAIN ORGAN SEGMENTATION WITH 3D FULLY CONVOLUTIONAL NEURAL NETWORK FOR RADIATION THERAPY TREATMENT PLANNING." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2020 (2020): 758-762. doi: https://doi.org/10.1109/isbi45749.2020.9098485
Duanmu H, Kim J, Kanakaraj P, Wang A, Joshua J, Kong J, Wang F. AUTOMATIC BRAIN ORGAN SEGMENTATION WITH 3D FULLY CONVOLUTIONAL NEURAL NETWORK FOR RADIATION THERAPY TREATMENT PLANNING. Proc IEEE Int Symp Biomed Imaging. 2020 Apr;2020:758-762. doi: 10.1109/isbi45749.2020.9098485. Epub 2020 May 22. PMID: 32802270; PMCID: PMC7427623.
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iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures.

Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Liang Y, Kong J, Vo H, Wang F.
PMID: 33977292
Proc ACM SIGSPATIAL Int Conf Adv Inf. 2017 Nov;2017. doi: 10.1145/3139958.3139961.

Recent advances in digital pathology make it possible to support 3D tissue-based investigation of human diseases at extremely high resolutions. Exploring spatial relationships and patterns among massive 3D micro-anatomic biological objects such as blood vessels and cells derived from...

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Liang Y, Kong J, Vo H, et al. iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures. Proc ACM SIGSPATIAL Int Conf Adv Inf. 2017;2017doi: 10.1145/3139958.3139961.
Liang, Y., Kong, J., Vo, H., & Wang, F. (2017). iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures. Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017. https://doi.org/10.1145/3139958.3139961
Liang, Yanhui, et al. "iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures." Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems vol. 2017 (2017). doi: https://doi.org/10.1145/3139958.3139961
Liang Y, Kong J, Vo H, Wang F. iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures. Proc ACM SIGSPATIAL Int Conf Adv Inf. 2017 Nov;2017. doi: 10.1145/3139958.3139961. PMID: 33977292; PMCID: PMC8110205.
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LIVER STEATOSIS SEGMENTATION WITH DEEP LEARNING METHODS.

Proceedings. IEEE International Symposium on Biomedical Imaging

Guo X, Wang F, Teodoro G, Farris AB, Kong J.
PMID: 32670464
Proc IEEE Int Symp Biomed Imaging. 2019 Apr;2019:24-27. doi: 10.1109/isbi.2019.8759600. Epub 2019 Jul 11.

Liver steatosis is known as the abnormal accumulation of lipids within cells. An accurate quantification of steatosis area within the liver histopathological microscopy images plays an important role in liver disease diagnosis and transplantation assessment. Such a quantification analysis...

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Guo X, Wang F, Teodoro G, et al. LIVER STEATOSIS SEGMENTATION WITH DEEP LEARNING METHODS. Proc IEEE Int Symp Biomed Imaging. 2019;2019:24-27doi: 10.1109/isbi.2019.8759600.
Guo, X., Wang, F., Teodoro, G., Farris, A. B., & Kong, J. (2019). LIVER STEATOSIS SEGMENTATION WITH DEEP LEARNING METHODS. Proceedings. IEEE International Symposium on Biomedical Imaging, 201924-27. https://doi.org/10.1109/isbi.2019.8759600
Guo, Xiaoyuan, et al. "LIVER STEATOSIS SEGMENTATION WITH DEEP LEARNING METHODS." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2019 (2019): 24-27. doi: https://doi.org/10.1109/isbi.2019.8759600
Guo X, Wang F, Teodoro G, Farris AB, Kong J. LIVER STEATOSIS SEGMENTATION WITH DEEP LEARNING METHODS. Proc IEEE Int Symp Biomed Imaging. 2019 Apr;2019:24-27. doi: 10.1109/isbi.2019.8759600. Epub 2019 Jul 11. PMID: 32670464; PMCID: PMC7363395.
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[No title available]

Distributed and parallel databases

Vo H, Kong J, Teng D, Liang Y, Aji A, Teodoro G, Wang F.
PMID: 31217669
Distrib Parallel Databases. 2019 Jun;37(2):251-272. doi: 10.1007/s10619-018-7237-1. Epub 2018 Jul 30.

Recent advancements in systematic analysis of high resolution whole slide images have increase efficiency of diagnosis, prognosis and prediction of cancer and important diseases. Due to the enormous sizes and dimensions of whole slide images, the analysis requires extensive...

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Vo H, Kong J, Teng D, et al. . Distrib Parallel Databases. 2018;37(2):251-272doi: 10.1007/s10619-018-7237-1.
Vo, H., Kong, J., Teng, D., Liang, Y., Aji, A., Teodoro, G., & Wang, F. (2019). . Distributed and parallel databases, 37(2), 251-272. https://doi.org/10.1007/s10619-018-7237-1
Vo, Hoang, et al. "." Distributed and parallel databases vol. 37,2 (2019): 251-272. doi: https://doi.org/10.1007/s10619-018-7237-1
Vo H, Kong J, Teng D, Liang Y, Aji A, Teodoro G, Wang F. . Distrib Parallel Databases. 2019 Jun;37(2):251-272. doi: 10.1007/s10619-018-7237-1. Epub 2018 Jul 30. PMID: 31217669; PMCID: PMC6583906.
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Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems.

Proceedings. IEEE International Conference on Cluster Computing

Barreiros W, Teodoro G, Kurc T, Kong J, Melo ACMA, Saltz J.
PMID: 29081725
Proc IEEE Int Conf Clust Comput. 2017 Sep;2017:25-35. doi: 10.1109/CLUSTER.2017.28. Epub 2017 Sep 26.

We investigate efficient sensitivity analysis (SA) of algorithms that segment and classify image features in a large dataset of high-resolution images. Algorithm SA is the process of evaluating variations of methods and parameter values to quantify differences in the...

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Barreiros W, Teodoro G, Kurc T, et al. Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems. Proc IEEE Int Conf Clust Comput. 2017;2017:25-35doi: 10.1109/CLUSTER.2017.28.
Barreiros, W., Teodoro, G., Kurc, T., Kong, J., Melo, A. C. M. A., & Saltz, J. (2017). Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems. Proceedings. IEEE International Conference on Cluster Computing, 201725-35. https://doi.org/10.1109/CLUSTER.2017.28
Barreiros, Willian, et al. "Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems." Proceedings. IEEE International Conference on Cluster Computing vol. 2017 (2017): 25-35. doi: https://doi.org/10.1109/CLUSTER.2017.28
Barreiros W, Teodoro G, Kurc T, Kong J, Melo ACMA, Saltz J. Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems. Proc IEEE Int Conf Clust Comput. 2017 Sep;2017:25-35. doi: 10.1109/CLUSTER.2017.28. Epub 2017 Sep 26. PMID: 29081725; PMCID: PMC5658136.
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DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES.

Proceedings. IEEE International Symposium on Biomedical Imaging

Rossetti BJ, Wang F, Zhang P, Teodoro G, Brat DJ, Kong J.
PMID: 28804569
Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:424-428. doi: 10.1109/ISBI.2017.7950552. Epub 2017 Jun 19.

High-throughput serial histology imaging provides a new avenue for the routine study of micro-anatomical structures in a 3D space. However, the emergence of serial whole slide imaging poses a new registration challenge, as the gigapixel image size precludes the...

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Rossetti BJ, Wang F, Zhang P, et al. DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES. Proc IEEE Int Symp Biomed Imaging. 2017;2017:424-428doi: 10.1109/ISBI.2017.7950552.
Rossetti, B. J., Wang, F., Zhang, P., Teodoro, G., Brat, D. J., & Kong, J. (2017). DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES. Proceedings. IEEE International Symposium on Biomedical Imaging, 2017424-428. https://doi.org/10.1109/ISBI.2017.7950552
Rossetti, Blair J, et al. "DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2017 (2017): 424-428. doi: https://doi.org/10.1109/ISBI.2017.7950552
Rossetti BJ, Wang F, Zhang P, Teodoro G, Brat DJ, Kong J. DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:424-428. doi: 10.1109/ISBI.2017.7950552. Epub 2017 Jun 19. PMID: 28804569; PMCID: PMC5550903.
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Application Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs: A Case Study with Microscopy Image Analysis.

The international journal of high performance computing applications

Teodoro G, Kurc T, Andrade G, Kong J, Ferreira R, Saltz J.
PMID: 28239253
Int J High Perform Comput Appl. 2017 Jan;31(1):32-51. doi: 10.1177/1094342015594519. Epub 2015 Jul 27.

We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core-MIC) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core operations of the application. We...

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Teodoro G, Kurc T, Andrade G, et al. Application Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs: A Case Study with Microscopy Image Analysis. Int J High Perform Comput Appl. 2015;31(1):32-51doi: 10.1177/1094342015594519.
Teodoro, G., Kurc, T., Andrade, G., Kong, J., Ferreira, R., & Saltz, J. (2017). Application Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs: A Case Study with Microscopy Image Analysis. The international journal of high performance computing applications, 31(1), 32-51. https://doi.org/10.1177/1094342015594519
Teodoro, George, et al. "Application Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs: A Case Study with Microscopy Image Analysis." The international journal of high performance computing applications vol. 31,1 (2017): 32-51. doi: https://doi.org/10.1177/1094342015594519
Teodoro G, Kurc T, Andrade G, Kong J, Ferreira R, Saltz J. Application Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs: A Case Study with Microscopy Image Analysis. Int J High Perform Comput Appl. 2017 Jan;31(1):32-51. doi: 10.1177/1094342015594519. Epub 2015 Jul 27. PMID: 28239253; PMCID: PMC5319667.
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AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES.

Proceedings. IEEE International Symposium on Biomedical Imaging

Kong J, Wang F, Teodoro G, Liang Y, Zhu Y, Tucker-Burden C, Brat DJ.
PMID: 26405506
Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:1212-1215. doi: 10.1109/ISBI.2015.7164091.

A large number of cell-oriented cancer investigations require an effective and reliable cell segmentation method on three dimensional (3D) fluorescence microscopic images for quantitative analysis of cell biological properties. In this paper, we present a fully automated cell segmentation...

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Kong J, Wang F, Teodoro G, et al. AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES. Proc IEEE Int Symp Biomed Imaging. 2015;2015:1212-1215doi: 10.1109/ISBI.2015.7164091.
Kong, J., Wang, F., Teodoro, G., Liang, Y., Zhu, Y., Tucker-Burden, C., & Brat, D. J. (2015). AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES. Proceedings. IEEE International Symposium on Biomedical Imaging, 20151212-1215. https://doi.org/10.1109/ISBI.2015.7164091
Kong, Jun, et al. "AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES." Proceedings. IEEE International Symposium on Biomedical Imaging vol. 2015 (2015): 1212-1215. doi: https://doi.org/10.1109/ISBI.2015.7164091
Kong J, Wang F, Teodoro G, Liang Y, Zhu Y, Tucker-Burden C, Brat DJ. AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:1212-1215. doi: 10.1109/ISBI.2015.7164091. PMID: 26405506; PMCID: PMC4578315.
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Showing 1 to 12 of 22 entries