Selected Publications

Recent Journal Papers (2019 - 2022)

  1. Chen X, Wang X, Zhang K, Fung K, Thai T, Moore K, Mannel R, Liu H, Zheng B, Qiu Y, Recent advances and clinical applications of deep learning in medical image analysis, Medical Imaging Analysis, 2022; 79:102444.
  2. Li Y, Yuan W, Fan M, Zheng B, Li L, Prediction of short-term breast cancer risk with fusion of CC- and MLO-based risk models in four-view mammograms, Journal of Digital Imaging, 2022; DOI: 10.1007/s10278-019-00266-4.
  3. Danala G, Ray B, Desai M, Heidari M, Mirniaharikandehei S, Maryada S, Zheng B, Developing new quantitative CT image markers to predict prognosis of acute ischemic stroke patients, Journal of X-ray Science and Technology, 2022; 30:459-475.
  4. Jones MA, Faiz R, Qiu Y, Zheng B, Improving mammography lesion classification by optimal fusion of handcrafted and deep learning features, Physics in Medicine and Biology, 2022; 67(5):054001.
  5. Danala G, Desai M, Ray B, Heidari M, Maryada SKR, Prodan CI, Zheng B, Applying quantitative radiographic image markers to predict clinical complications after aneurysmal subarachnoid hemorrhage: A pilot study, Annals of Biomedical Engineering, 2022; 50(4):413-425.
  6. Nouh CD, Ray B, Xu C, Zheng B, Danala G, Koriesh A, Hollabaugh K, Gordon D, Sidorov EV, Quantitative analysis of stress-induced hyperglycemia and intracranial blood volumes for predicting mortality after intracerebral hemorrhage, Translational Stroke Research, 2022; DOI:10.1007/s12975-022-00985-x.
  7. Gai T, Thai T, Jones M, Jo J, Zheng B, Applying a radiomics-based CAD scheme to classify between malignant and benign pancreatic tumors using CT images, Journal of X-ray Science and Technology, 2022; 30(2):377-388.
  8. Zhang K, Lu X, Chen X, Zhang R, Fung KM, Liu H, Zheng B, Li S, Qiu Y, Using Fourier ptychography microscopy to achieve high-resolution chromosome imaging: an initial evaluation, Journal of Biomedical Optics, 2022; 27:016504.
  9. Ghani M, Omoumi F, Wu X, Fajardo L, Zheng B, Liu H, Evaluation and comparison of a CdTe based photon counting detector with an energy integrating detector for X-ray phase sensitive imaging of breast cancer, Journal of X-ray Science and Technology, 2022; 30(2):207-219.
  10. Ghani M, Fajardo L, Omoumi F, Yan A, Jenkins P, Wong M, Li Y, Hills S, Zheng B, Wu X, Peterson M, Callahan E, Liu H, A phase sensitive X-ray breast tomosynthesis system: preliminary patient images with cancer lesions, Physics in Medicine and Biology, 2021; 66:21LT01.
  11. Zuo T, Zheng Y, He L, Chen T, Zheng B, Zheng S, You J, Li X, Liu R, Bai J, Si S, Wang Y, Zhang S, Wang L, Chen J, Automated classification of papillary renal cell carcinoma and chromophobe renal cell carcinoma based on a small computed tomography imaging dataset using deep learning, Frontiers in Oncology, 2021; 11:746750.
  12. Shi T, Jiang H, Zheng B, C2MA-Net: Cross-modal cross-attention network for acute ischemic stroke lesion segmentation based on CT perfusion scans, IEEE Transaction on Biomedical Engineering, 2022; 69:108-118.
  13. Buechel ME, Enserro D, Burger RA, Brady MF, Wade K, Secord A, Nixon AB, Mirniaharikandehei S, Liu H, Zheng B, O’Malley DM, Gray H, Tewari KS, Mannel RS, Birrer MJ, Moore KN, Correlation of imaging and plasma based biomarkers to predict response to bevacizumab in epithelial ovarian cancer (EOC), Gynecologic Oncology, 2021; 161:382-388.
  14. Heidari M, Lakshmivarahan S, Mirniaharikandehei S, Danala G, Maryada SK, Liu H, Zheng B, Applying a random projection algorithm to optimize machine learning model for breast lesion classification, IEEE Transaction on Biomedical Engineering, 2021; 68(9):2764-2775.
  15. Ghani M, Wu X, Fajardo L, Jing Z, Wong M, Zheng B, Omoumi F, Li Y, Yan A, Jenkins P, Hills S, Linstroth L, Liu H, Development and pre-clinical evaluation of a patient-specific high energy X-ray phase sensitive breast tomosynthesis system, Medical Physics 2021; 48:2511-2520.
  16. Mirniaharikandehei S, Heidari M, Danala G, Lakshmivarahan S, Zheng B, Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images, Computer Methods and Programs in Biomedicine, 2021; 200:105937.
  17. Wang L, Gong J, Huang X, Lin G, Zheng B, Chen J, Xie J, Lin R, Duan Q, Lin W, CT-based radiomics nomogram for preoperative prediction of No.10 lymph nodes metastasis in advanced proximal gastric cancer, European Journal of Surgical Oncology 2021; 47(6):1458-1465.
  18. Omoumi FH, Ghani MU, Wong MD, Li Y, Zheng B, Yan A, Jenkins PA, Wu X, Liu H, The potential of utilizing mid-energy X-rays for in-line phase sensitive breast cancer imaging, Biomedical Spectroscopy and Imaging, 2020; 9:89-102.
  19. Heidari M, Mirniaharkandehei S, Khuzani AZ, Danala G, Qiu Y, Zheng B, Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms, International Journal of Medical Informatics 2020; 144:104284.
  20. Chen X, Liu W, Thai TC, Castellano T, Gunderson CC, Moore K, Mannel RS, Liu H, Zheng B, Qiu Y, Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients, Computer Methods and Programs in Biomedicine 2020; 197:105759.
  21. Shi T, Jiang H, Zheng B, A stacked generalized U-shape network based on zoom strategy and its application in biomedical image segmentation, Computer Methods and Programs in Biomedicine 2020; 197:105678.
  22. Yang A, Huang H, Zheng B, Li S. Gan H, Chen C, Yang X, Xue Y, An automatic recognition framework for sow daily behaviours based on motion and image analysis, Biosystems Engineering 2020; 192:56-71.
  23. Gong J, Liu J, Hao W, Nie S, Zheng B, Wang S, Peng W, A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images, European Radiology 2020; 30:1847-1855.
  24. O’Connor KP, Hathidara M, Danala G, Xu C, McCoy TM, Sidorow EV, Zheng B, Bohnstedt BN, Ray B, Predicting clinical outcome after mechanical thrombectomy: The GADIS (Gender, Age, Diabetes Mellitus History, Infarct Volume, and Sex) score, Would Neurosurgery 2020; 134:e1130-e1142.
  25. Porwal P, Pachade S, Kokare M, Deshmukh G, Son J, Bae W, Liu L, Wang J, Liu X, Gao L, Wu T, Xiao J, Wang F, Yin B, Wang Y, Danala G, He L, Choi Y, Lee Y, Jung S, Li Z, Sui X, Wu J, Li X, Zhou T, Toth J, Baren A, Kori A, Chennamsetty S, Safwan M, Alex V, Lyu X, Cheng L, Chu Q, Li P, Ji X, Zhang S, Shen Y, Dai L, Saha O, Sathish R, Melo T, Araujo T, Harangi B, Sheng B, Fang R, Sheet D, Hajdu A, Zheng Y, Mendonca A, Zhang S, Campilho A, Zheng B, Shen D, Giancardo L, Quellec G, Meriaudeau F, IDRid: Diabetic retinopathy – Segmentation and grading challenge, Medical Image Analysis 2020; 59:101561.
  26. Zhu X, Chen C, Zheng B, Yang X, Gan H, Zheng C, Yang A, Mao L, Xue Y, Automatic recognition of lactating sow postures by refined two-stream RGB-D faster R-CNN, Biosystems Engineering 2020; 189:116-132.
  27. Heidari M, Mirniaharikandehei S, Liu W, Hollingsworth AB, Liu H, Zheng B, Development and assessment of a new global mammographic image feature analysis scheme to predict likelihood of malignant cases, IEEE Transactions on Medical Imaging 2020; 39:1235-1244.
  28. Gillen J, Mills KA, Dvorak J, Zheng B, Thai T, Salani R, Cosgrove CM, Davidson B, Thaker PH, Moore KN, Imaging biomarkers of adiposity and sarcopenia as potential predictors for overall survival among patients with endometrial cancer treated with bevacizumab, Gynecologic Oncology Reports 2019; 30:100502.
  29. Ray B, Ross SR, Danala G, Aghaei F, Nouh CD, Ford L, Hollabaugh KM, Karfonta BN, Santucci JA, Cornwell BO, Bohnstedt BN, Zheng B, Dale GL, Prodan CI, Systemic response of coated-platelet and peripheral blood in flammatory cell indices after aneurysmal subarachnoid hemorrhage and long-term clinical outcome, Journal of Critical Care, 2019; 52:1-9.
  30. Zheng B, Qiu Y, Aghaei F, Mirniaharikandehei S, Heidari M, Danala G, Developing global image feature analysis models to predict cancer risk and prognosis, Visual Computing for Industry, Biomedicine, and Art 2019; 2:58-71.
  31. Slaughter Wade KN, Brady MF, Thai T, Wang Y, Zheng B, Salani R, Tewari KS, Gray HJ, Bakkum-Gamez JN, Burger RA, Moore KN, Bookman MA, Measurements of adiposity as prognostic biomarkers for survival with anti-angiogenic treatment in epithelial ovarian cancer: An NRG Oncology/Gynecologic Oncology Group ancillary data analysis of GOG 218, Gynecologic Oncology 2019; 155:69-74.
  32. Li Y, Fan M, Liu S, Zheng B, Li L, Prediction of short-term breast cancer risk based on deep convolutional neural networks in mammography, Journal of Medical Imaging and Health Informatics, 2019; 9(8):1663-1672.
  33. Chen X, Khuzani AZ, Hollingsworth AB, Liu H, Zheng B, Qiu Y, Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer, Computer Methods and Programs in Biomedicine, 2019; 179:104995.
  34. Wang K, Patel B.K., Wang L, Wu T, Zheng B, Li J, A dual-mode deep learning transfer learning (D2TL) system for breast cancer detection using contrast enhanced digital mammograms, IISE Transactions on Healthcare Systems Engineering, 2019; 9:357-370.
  35. Mirniaharikandehei S, VanOsdol J, Heidari M, Danala G, Sethuraman SN. Ranjan A, Zheng B, Developing a quantitative ultrasound image feature analysis scheme to assess tumor treatment efficacy using a mouse model, Scientific Reports, 2019; 9:7293.
  36. Song J, Tian J, Zhang L, Qu X, Qian W, Zheng B, Zhang L, Zhao J, Niu M, Zhou M, Cui L, Liu Y, Zhao M, Development and validation of a prognostic index for efficacy evaluation and prognosis of first-line chemotherapy in stage III–IV lung squamous cell carcinoma, European Radiology 2019; 29:2388-2398.
  37. Yin K, Yan S, Song C, Zheng B, A robust method for segmenting pectoral muscle in mediolateral oblique (MLO) mammograms, International Journal of Computer Assisted Radiology and Surgery, 2019; 14:237-248.
  38. Santucci J, Ross S, Greemert J, Aghaei F, Ford L, Hollabaugh K, Conwell B, Wu D, Zheng B, Bohnstedt B, Ray B, Radiological estimation of intracranial blood volume and occurrence of hydrocephalus determines stress-induced hyperglycemia after aneurysmal subarachnoid hemorrhage, Translational Stroke Research 2019; 10:327-337.

Complete list of my publications (research papers and patents) and the detailed citation information can be found in Google Scholar Webpage.

https://scholar.google.com/citations?user=FnKrwz0AAAAJ&hl=en

Research Outreach Arcticle – Assessing Performance of Computer-Aided Diagnosis of Breast Cancer

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