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ORCIDDmitry B. Goldgof
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- affiliation: University of South Florida, Tampa, FL, USA
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2020 – today
- 2024
[j82]Jacqueline Hausmann
, Md Sirajus Salekin, Ghada Zamzmi, Peter R. Mouton, Stephanie Prescott, Thao Ho, Yu Sun, Dmitry B. Goldgof:
Accurate Neonatal Face Detection for Improved Pain Classification in the Challenging NICU Setting. IEEE Access 12: 49122-49133 (2024)- [j81]Saeed S. Alahmari, Lawrence O. Hall, Peter R. Mouton, Dmitry B. Goldgof:
Repeatability of Fine-Tuning Large Language Models Illustrated Using QLoRA. IEEE Access 12: 153221-153231 (2024) - [j80]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7458-7477 (2024) - [c157]Manas Sanjay Pakalapati, Dmitry B. Goldgof, Lawrence O. Hall, Ghada Zamzmi:
Anonymized Identity Tracking: Privacy Preserving Facial Encoding. CBMS 2024: 89-93 - [c156]Abhiram Kandiyana, Peter R. Mouton, Lawrence O. Hall, Dmitry B. Goldgof:
Active Prompting of Vision Language Models for Human-in-the-loop Classification and Explanation of Microscopy Images. CBMS 2024: 205-212 - [c155]Md Imran Hossain, Ghada Zamzmi, Peter R. Mouton, Yu Sun, Dmitry B. Goldgof:
Enhancing Concept-Based Explanation with Vision-Language Models. CBMS 2024: 219-224 - [i13]Shashwat Kumar, Francis Hahn, Xinming Ou, Dmitry B. Goldgof, Lawrence O. Hall, Jay Ligatti, S. Raj Rajagopalan, Armin Ziaie Tabari:
A Preliminary Study on Using Large Language Models in Software Pentesting. CoRR abs/2401.17459 (2024) - 2023
- [c154]Md Imran Hossain, Ghada Zamzmi, Peter R. Mouton, Yu Sun, Dmitry B. Goldgof:
Enhancing Neonatal Pain Assessment Transparency via Explanatory Training Examples Identification. CBMS 2023: 311-316 - [c153]Hunter Morera, Palak Dave, Saeed S. Alahmari, Yaroslav Kolinko, Lawrence O. Hall, Dmitry B. Goldgof, Peter R. Mouton:
MIMO YOLO - A Multiple Input Multiple Output Model for Automatic Cell Counting. CBMS 2023: 827-831 - [c152]Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath:
Unsupervised Prostate Cancer Histopathology Image Segmentation via Meta-Learning. CBMS 2023: 838-844 - [c151]Palak Dave, Yaroslav Kolinko, Hunter Morera, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
MIMO U-Net: efficient cell segmentation and counting in microscopy image sequences. Digital and Computational Pathology 2023 - 2022
- [j79]Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Ryan Fogarty:
Achieving Multisite Generalization for CNN-Based Disease Diagnosis Models by Mitigating Shortcut Learning. IEEE Access 10: 78726-78738 (2022) - [j78]Hunter Morera, Roshan Warman, Azubuogu Anudu, Chukwudumebi Uche, Ivana Radosavljevic, Nikhil Reddy, Ahan Kayastha, Niharika Baviriseaty, Rahul Mhaskar, Andrew A. Borkowski, Patrick Brady, Satish Singh, Gerard Mullin, José Lezama, Lawrence O. Hall, Dmitry B. Goldgof, Gitanjali Vidyarthi:
Reduction of Video Capsule Endoscopy Reading Times Using Deep Learning with Small Data. Algorithms 15(10): 339 (2022) - [j77]Ghada Zamzmi, Chih-Yun Pai, Dmitry B. Goldgof, Rangachar Kasturi, Terri Ashmeade, Yu Sun:
A Comprehensive and Context-Sensitive Neonatal Pain Assessment Using Computer Vision. IEEE Trans. Affect. Comput. 13(1): 28-45 (2022) - [c150]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Peter R. Mouton, Kanwaljeet J. S. Anand, Terri Ashmeade, Stephanie Prescott, Yangxin Huang, Yu Sun:
Attentional Generative Multimodal Network for Neonatal Postoperative Pain Estimation. MICCAI (3) 2022: 749-759 - [c149]Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath:
Survival time prediction from unannotated lung cancer histopathology images. Digital and Computational Pathology 2022 - [c148]Hunter Morera, Palak Dave, Yaroslav Kolinko, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Classification of global microglia proliferation based on deep learning with local images. Image Processing 2022 - [d1]Kaoutar Ben Ahmed, Gregory M. Goldgof, Rahul Paul, Dmitry B. Goldgof, Lawrence O. Hall:
COVID-19 and Pneumonia Xrays. IEEE DataPort, 2022
- [i12]Jacqueline Hausmann, Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Yu Sun:
Robust Neonatal Face Detection in Real-world Clinical Settings. CoRR abs/2204.00655 (2022) - 2021
- [j76]Kaoutar Ben Ahmed, Gregory M. Goldgof, Rahul Paul, Dmitry B. Goldgof, Lawrence O. Hall:
Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification. IEEE Access 9: 72970-72979 (2021) - [j75]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
Multimodal spatio-temporal deep learning approach for neonatal postoperative pain assessment. Comput. Biol. Medicine 129: 104150 (2021) - [j74]Yoganand Balagurunathan, Andrew Beers, Michael F. McNitt-Gray, Lubomir M. Hadjiiski, Sandy Napel, Dmitry B. Goldgof, Gustavo Pérez, Pablo Arbeláez, Alireza Mehrtash, Tina Kapur, Ehwa Yang, Jung Won Moon, Gabriel Bernardino Perez, Ricard Delgado-Gonzalo, Mohammad Mehdi Farhangi, Amir A. Amini, Renkun Ni, Xue Feng, Aditya Bagari, Kiran Vaidhya, Benjamin Veasey, Wiem Safta, Hichem Frigui, Joseph Enguehard, Ali Gholipour, Laura Silvana Castillo, Laura Alexandra Daza, Paul F. Pinsky, Jayashree Kalpathy-Cramer, Keyvan Farahani:
Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge. IEEE Trans. Medical Imaging 40(12): 3748-3761 (2021) - [c147]Rahul Paul, Sherzod Kariev, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Deep radiomics: deep learning on radiomics texture images. Computer-Aided Diagnosis 2021 - [c146]Sidharth Srivatsav Sribhashyam, Md Sirajus Salekin, Dmitry B. Goldgof, Ghada Zamzmi, Mark Last, Yu Sun:
Pattern Recognition in Vital Signs Using Spectrograms. SMC 2021: 1133-1138 - [i11]Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Gregory M. Goldgof, Rahul Paul:
Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders. CoRR abs/2102.04300 (2021) - [i10]Sidharth Srivatsav Sribhashyam, Md Sirajus Salekin, Dmitry B. Goldgof, Ghada Zamzmi, Yu Sun:
Pattern Recognition in Vital Signs Using Spectrograms. CoRR abs/2108.03168 (2021) - 2020
- [j73]Saeed S. Alahmari, Dmitry B. Goldgof, Peter R. Mouton, Lawrence O. Hall:
Challenges for the Repeatability of Deep Learning Models. IEEE Access 8: 211860-211868 (2020) - [j72]Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. Comput. Biol. Medicine 122: 103882 (2020) - [j71]Diego Fabiano, Shaun J. Canavan, Heather Agazzi, Saurabh Hinduja, Dmitry B. Goldgof:
Gaze-based classification of autism spectrum disorder. Pattern Recognit. Lett. 135: 204-212 (2020) - [c145]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
First Investigation into the Use of Deep Learning for Continuous Assessment of Neonatal Postoperative Pain. FG 2020: 415-419 - [c144]Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Mitigating Adversarial Attacks on Medical Image Understanding Systems. ISBI 2020: 1517-1521 - [i9]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
First Investigation Into the Use of Deep Learning for Continuous Assessment of Neonatal Postoperative Pain. CoRR abs/2003.10601 (2020) - [i8]Lawrence O. Hall, Rahul Paul, Dmitry B. Goldgof, Gregory M. Goldgof:
Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset. CoRR abs/2004.02060 (2020) - [i7]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
Multimodal Spatio-Temporal Deep Learning Approach for Neonatal Postoperative Pain Assessment. CoRR abs/2012.02175 (2020)
2010 – 2019
- 2019
- [j70]Ghada Zamzmi, Rahul Paul, Md Sirajus Salekin, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
Convolutional Neural Networks for Neonatal Pain Assessment. IEEE Trans. Biom. Behav. Identity Sci. 1(3): 192-200 (2019) - [c143]Cagri Cetin, Dmitry B. Goldgof, Jay Ligatti:
SQL-Identifier Injection Attacks. CNS 2019: 151-159 - [c142]Jean-Baptiste Subils, Joseph Perez, Peiwei Liu, Shamaria Engram, Cagri Cetin, Dmitry B. Goldgof, Natalie C. Ebner, Daniela Oliveira, Jay Ligatti:
A Dual-Task Interference Game-Based Experimental Framework for Comparing the Usability of Authentication Methods. HSI 2019: 95-100 - [c141]Ghada Zamzmi, Rahul Paul, Dmitry B. Goldgof, Rangachar Kasturi, Yu Sun:
Pain Assessment From Facial Expression: Neonatal Convolutional Neural Network (N-CNN). IJCNN 2019: 1-7 - [c140]Chih-Yun Pai, Hunter Morera, Sudeep Sarkar, Kimberly S. Hall, Linda J. Cowan, Peter A. Toyinbo, Matthew J. Peterson, Dmitry B. Goldgof:
Automatic pressure ulcer measurement using RGB-D data. Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095320 - [c139]Rahul Paul, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. Computer-Aided Diagnosis 2019: 109503Z - [c138]Jay Ligatti, Cagri Cetin, Shamaria Engram, Jean-Baptiste Subils, Dmitry B. Goldgof:
Coauthentication. SAC 2019: 1906-1915 - [c137]Kaoutar Ben Ahmed, Lawrence O. Hall, Renhao Liu, Robert A. Gatenby, Dmitry B. Goldgof:
Neuroimaging Based Survival Time Prediction of GBM Patients Using CNNs from Small Data. SMC 2019: 1331-1335 - [c136]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
Multi-Channel Neural Network for Assessing Neonatal Pain from Videos. SMC 2019: 1551-1556 - [c135]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Automatic Cell Counting using Active Deep Learning and Unbiased Stereology. SMC 2019: 1708-1713 - [i6]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton:
Iterative Deep Learning Based Unbiased Stereology With Human-in-the-Loop. CoRR abs/1901.04355 (2019) - [i5]Md Sirajus Salekin, Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
Multi-Channel Neural Network for Assessing Neonatal Pain from Videos. CoRR abs/1908.09254 (2019) - [i4]Md Sirajus Salekin, Ghada Zamzmi, Rahul Paul, Dmitry B. Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun:
Harnessing the Power of Deep Learning Methods in Healthcare: Neonatal Pain Assessment from Crying Sound. CoRR abs/1909.02543 (2019) - 2018
- [j69]Saeed S. Alahmari, Dmitry Cherezov, Dmitry B. Goldgof, Lawrence O. Hall, Robert J. Gillies, Matthew B. Schabath:
Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access 6: 77796-77806 (2018) - [j68]Ruicong Zhi, Ghada Zamzmi, Dmitry B. Goldgof, Terri Ashmeade, Tingting Li, Yu Sun:
Infants' Pain Recognition Based on Facial Expression: Dynamic Hybrid Descriptions. IEICE Trans. Inf. Syst. 101-D(7): 1860-1869 (2018) - [c134]Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Yu Sun:
Toward Ubiquitous Assessment of Neonates' Health Condition. UbiComp/ISWC Adjunct 2018: 952-955 - [c133]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton:
Iterative Deep Learning Based Unbiased Stereology with Human-in-the-Loop. ICMLA 2018: 665-670 - [c132]Rahul Paul, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath, Robert J. Gillies:
Predicting Nodule Malignancy using a CNN Ensemble Approach. IJCNN 2018: 1-8 - [c131]Rahul Paul, Ying Liu, Qian Li, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Matthew B. Schabath, Robert J. Gillies:
Representation of Deep Features using Radiologist defined Semantic Features. IJCNN 2018: 1-7 - [c130]Rahul Paul, Muhammad Shafiq-ul-Hassan, Eduardo G. Moros, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Stability of deep features across CT scanners and field of view using a physical phantom. Computer-Aided Diagnosis 2018: 105753P - [i3]Ghada Zamzmi, Dmitry B. Goldgof, Rangachar Kasturi, Yu Sun:
Neonatal Pain Expression Recognition Using Transfer Learning. CoRR abs/1807.01631 (2018) - [i2]Ghada Zamzmi, Gabriel Ruiz, Matthew Shreve, Dmitry B. Goldgof, Rangachar Kasturi, Sudeep Sarkar:
A method to Suppress Facial Expression in Posed and Spontaneous Videos. CoRR abs/1810.02401 (2018) - 2017
- [j67]Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A framework for nucleus and overlapping cytoplasm segmentation in cervical cytology extended depth of field and volume images. Comput. Medical Imaging Graph. 59: 38-49 (2017) - [c129]Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Renhao Liu, Robert A. Gatenby:
Fine-tuning convolutional deep features for MRI based brain tumor classification. Computer-Aided Diagnosis 2017: 101342E - [c128]Ghada Zamzmi, Chih-Yun Pai, Dmitry B. Goldgof, Rangachar Kasturi, Yu Sun, Terri Ashmeade:
Automated Pain Assessment in Neonates. SCIA (2) 2017: 350-361 - [c127]Renhao Liu, Lawrence O. Hall, Kevin W. Bowyer, Dmitry B. Goldgof, Robert A. Gatenby, Kaoutar Ben Ahmed:
Synthetic minority image over-sampling technique: How to improve AUC for glioblastoma patient survival prediction. SMC 2017: 1357-1362 - [c126]Ekambaram Rajmadhan, Dmitry B. Goldgof, Lawrence O. Hall:
Finding label noise examples in large scale datasets. SMC 2017: 2420-2424 - 2016
- [j66]Jayashree Kalpathy-Cramer, Binsheng Zhao, Dmitry B. Goldgof, Yuhua Gu, Xingwei Wang, Hao Yang, Yongqiang Tan, Robert J. Gillies, Sandy Napel:
A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study. J. Digit. Imaging 29(4): 476-487 (2016) - [j65]Ekambaram Rajmadhan, Sergiy Fefilatyev, Matthew Shreve, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi:
Active cleaning of label noise. Pattern Recognit. 51: 463-480 (2016) - [c125]Hady Ahmady Phoulady, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Automatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling. ICIP 2016: 2658-2662 - [c124]Ghada Zamzmi, Chih-Yun Pai, Dmitry B. Goldgof, Rangachar Kasturi, Terri Ashmeade, Yu Sun:
An approach for automated multimodal analysis of infants' pain. ICPR 2016: 4148-4153 - [c123]Renhao Liu, Lawrence O. Hall, Dmitry B. Goldgof, Mu Zhou, Robert A. Gatenby, Kaoutar Ben Ahmed:
Exploring deep features from brain tumor magnetic resonance images via transfer learning. IJCNN 2016: 235-242 - [c122]Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A new approach to detect and segment overlapping cells in multi-layer cervical cell volume images. ISBI 2016: 201-204 - [c121]Baishali Chaudhury, Mu Zhou, Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Robert J. Weinfurtner, Jennifer S. Drukteinis:
Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats. Computer-Aided Diagnosis 2016: 97850T - [c120]Hamidreza Farhidzadeh, Baishali Chaudhury, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development. Computer-Aided Diagnosis 2016: 97851H - [c119]Hamidreza Farhidzadeh, Joo Y. Kim, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Louis B. Harrison:
Classification of progression free survival with nasopharyngeal carcinoma tumors. Computer-Aided Diagnosis 2016: 97851I - [c118]Benjamin Geiger, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Robert A. Gatenby, Robert J. Gillies:
Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. Computer-Aided Diagnosis 2016: 978535 - [c117]Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Nucleus segmentation in histology images with hierarchical multilevel thresholding. Digital Pathology 2016: 979111 - [c116]Dmitry Cherezov, Samuel H. Hawkins, Dmitry B. Goldgof, Lawrence O. Hall, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath:
Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. SMC 2016: 1939-1944 - [c115]Rahul Paul, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies:
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. SMC 2016: 2570-2575 - [c114]Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Jacob G. Scott, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs. SMC 2016: 4549-4554 - [i1]Ghada Zamzmi, Chih-Yun Pai, Dmitry B. Goldgof, Rangachar Kasturi, Yu Sun, Terri Ashmeade:
Machine-based Multimodal Pain Assessment Tool for Infants: A Review. CoRR abs/1607.00331 (2016) - 2015
- [c113]Ghada Zamzmi, Gabriel Ruiz, Dmitry B. Goldgof, Rangachar Kasturi, Yu Sun, Terri Ashmeade:
Pain assessment in infants: Towards spotting pain expression based on infants' facial strain. FG 2015: 1-5 - [c112]Hamidreza Farhidzadeh, Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats. Computer-Aided Diagnosis 2015: 94141U - [c111]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby:
Imbalanced learning for clinical survival group prediction of brain tumor patients. Computer-Aided Diagnosis 2015: 94142K - [c110]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robin Russo, Robert J. Gillies, Robert A. Gatenby:
Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI. Computer-Aided Diagnosis 2015: 94142H - [c109]Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI. Computer-Aided Diagnosis 2015: 941415 - [c108]Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors. SMC 2015: 2164-2169 - [c107]Hailing Zhou, Dmitry B. Goldgof, Samuel H. Hawkins, Lei Wei, Ying Liu, Douglas C. Creighton, Robert J. Gillies, Lawrence O. Hall, Saeid Nahavandi:
A Robust Approach for Automated Lung Segmentation in Thoracic CT. SMC 2015: 2267-2272 - [c106]Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Texture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas. SMC 2015: 2798-2802 - 2014
- [j64]Samuel H. Hawkins, John N. Korecki, Yoganand Balagurunathan, Yuhua Gu, Virendra Kumar, Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies:
Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. IEEE Access 2: 1418-1426 (2014) - [j63]Matthew Shreve, Jesse Brizzi, Sergiy Fefilatyev, Timur Luguev, Dmitry B. Goldgof, Sudeep Sarkar:
Automatic expression spotting in videos. Image Vis. Comput. 32(8): 476-486 (2014) - [j62]Yoganand Balagurunathan, Virendra Kumar, Yuhua Gu, Jongphil Kim, Hua Wang, Ying Liu, Dmitry B. Goldgof, Lawrence O. Hall, René Korn, Binsheng Zhao, Lawrence H. Schwartz, Satrajit Basu, Steven Eschrich, Robert A. Gatenby, Robert J. Gillies:
Test-Retest Reproducibility Analysis of Lung CT Image Features. J. Digit. Imaging 27(6): 805-823 (2014) - [j61]Dmitry B. Goldgof, Xiaoyi Jiang, Olga Regina Pereira Bellon:
Special issue on depth image analysis. Pattern Recognit. Lett. 50: 1-2 (2014) - [j60]Matthew Shreve, Mauricio Pamplona, Timur Luguev, Dmitry B. Goldgof, Sudeep Sarkar:
High-resolution 3D surface strain magnitude using 2D camera and low-resolution depth sensor. Pattern Recognit. Lett. 50: 34-42 (2014) - [c105]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof:
Exploring Brain Tumor Heterogeneity for Survival Time Prediction. ICPR 2014: 580-585 - [c104]Jesse Brizzi, Dmitry B. Goldgof, Sudeep Sarkar, Matthew Shreve:
Optical Flow Based Expression Suppression in Video. ICPR 2014: 1817-1821 - [c103]Rangachar Kasturi, Dmitry B. Goldgof, Ekambaram Rajmadhan, Gill A. Pratt, Eric Krotkov, Douglas Hackett, Yang Ran, Qinfen Zheng, Rajeev Sharma, Mark Anderson, Mark Peot, Mario Aguilar, Deepak Khosla, Yang Chen, Kyungnam Kim, Lior Elazary, Randolph C. Voorhies, Daniel F. Parks, Laurent Itti:
Performance Evaluation of Neuromorphic-Vision Object Recognition Algorithms. ICPR 2014: 2401-2406 - [c102]Baishali Chaudhury, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis. Computer-Aided Diagnosis 2014: 90351V - [c101]Hamidreza Farhidzadeh, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Meera Raghavan, Robert A. Gatenby:
Prediction of treatment response and metastatic disease in soft tissue sarcoma. Computer-Aided Diagnosis 2014: 903518 - [c100]Hady Ahmady Phoulady, Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel:
Experiments with large ensembles for segmentation and classification of cervical cancer biopsy images. SMC 2014: 870-875 - [c99]Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction. SMC 2014: 2624-2629 - 2013
- [j59]Yuhua Gu, Virendra Kumar, Lawrence O. Hall, Dmitry B. Goldgof, Ching-Yen Li, René Korn, Claus Bendtsen, Emmanuel Rios Velazquez, Andre Dekker, Hugo J. W. L. Aerts, Philippe Lambin, Xiuli Li, Jie Tian, Robert A. Gatenby, Robert J. Gillies:
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. Pattern Recognit. 46(3): 692-702 (2013) - [c98]Maurício Pamplona Segundo, Sudeep Sarkar, Dmitry B. Goldgof, Luciano Silva, Olga Regina Pereira Bellon:
Continuous 3D Face Authentication Using RGB-D Cameras. CVPR Workshops 2013: 64-69 - [c97]Sergiy Fefilatyev, Matthew Shreve, Dmitry B. Goldgof:
Detection of the Vanishing Line of the Ocean Surface from Pairs of Scale-Invariant Keypoints. ICIAP (1) 2013: 161-169 - [c96]Baishali Chaudhury, Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel:
An Ensemble Algorithm Framework for Automated Stereology of Cervical Cancer. ICIAP (1) 2013: 823-832 - [c95]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby:
Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement. Computer-Aided Diagnosis 2013: 86702O - [c94]Henry Krewer, Benjamin Geiger, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Melvyn Tockman, Robert J. Gillies:
Effect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography. SMC 2013: 3887-3891 - [c93]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies:
A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients. SMC 2013: 4533-4538 - [e1]Xiaoyi Jiang, Olga Regina Pereira Bellon, Dmitry B. Goldgof, Takeshi Oishi:
Advances in Depth Image Analysis and Applications - International Workshop, WDIA 2012, Tsukuba, Japan, November 11, 2012, Revised Selected and Invited Papers. Lecture Notes in Computer Science 7854, Springer 2013, ISBN 978-3-642-40302-6 [contents] - 2012
- [j58]Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, John N. Korecki, Steven Eschrich:
Iterative Feature perturbation as a gene Selector for microarray Data. Int. J. Pattern Recognit. Artif. Intell. 26(5) (2012) - [c92]Baishali Chaudhury, Kurt Kramer, Daniel Elozory, Gerry Hernandez, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A novel algorithm for automated counting of stained cells on thick tissue sections. CBMS 2012: 1-6 - [c91]