Skip to main content

Research Updates at the Clinical Image Analysis Lab

  1. Prescott J, Donqing Z, Wang J, Mayr N, Yuh W, Saltz J, Gurcan MN, Cancer treatment outcome prediction by assessing temporal change: Application to cervical cancer, Accepted to SPIE Medical Imaging 2008, 16 - 21 February 2008, San Diego, California.
  2. Sertel O, Kong J, Lozanski G, Catalyurek U, Saltz J, Gurcan MN, Computerized microscopic image analysis of follicular lymphoma, Accepted to SPIE Medical Imaging 2008, 16 - 21 February 2008, San Diego, California.
  3. Sertel O, Kong J, Shimada H, Catalyurek U, Saltz J, Gurcan MN, Computer-aided prognosis of neuroblastoma: classification of stromal development on whole-slide images, Accepted to SPIE Medical Imaging 2008, 16 - 21 February 2008, San Diego, California.
  4. Kong J, Sertel O, Shimada H, Boyer K, Saltz J, Gurcan MN, A multi-resolution image analysis system for computer-assisted grading of neuroblastoma differentiation, Accepted to SPIE Medical Imaging 2008, 16 - 21 February 2008, San Diego, California.
  1. Prescott J, Zhang D, Wang J, Mayr N, Saltz J, Gurcan MN, Outcome Prediction for Radiation Treatment of Cervical Cancer by Assessing Tumor Heterogeneity and Temporal Change, Accepted to SIIM 2008, May 15-18, 2008, Seattle, WA.
  • Olcay Sertel will be presenting at the ICASSP meeting (http://www.icassp2008.org/) to be held in Las Vegas, NV, March 30-April 4, 2008. The paper to be presented:
  1. Sertel O, Kong J, Catalyurek U, Lozanski G, Shanaah A, Saltz J, Gurcan MN, Texture classification using nonlinear color quantization: Application to histopathological image analysis, Accepted to ICASSP 2008, March 30-April 4, 2008, Las Vegas, NV.
  • Olcay Sertel will be presenting at the USCAP meeting () to be held in Denver, CO, March 1-7, 2008. The paper to be presented:
  1. Sertel O, Kong J, Lozanski G, Shana'ah A, Gewirtz A, Racke F, Zhao J, Catalyurek U, Saltz J, Gurcan MN, Computer-assisted grading of follicular lymphoma: High grade differentiation, USCAP 2008, March 1-7, 2008, Denver, CO.
  • An article from our group has been accepted to the Archives of Pathology and Laboratory Medicine:
  1. Kong J, Sertel O, Shimada H, Boyer K, Saltz J, Gurcan MN, Computer-assisted grading of neuroblastic differentiation, Archives of Pathology & Laboratory Medicine, Accepted, 2008.
  • An article from our group has been accepted to the International Journal of Data Mining and Bioinformatics:
  1. Ruiz A, Sertel O, Ujaldon M, Catalyurek U, Saltz J, Gurcan MN, Pathological image analysis using the GPU: Stroma classification for Neuroblastoma, International Journal of Data Mining and Bioinformatics, accepted, 2008.
  • An article from our group has been accepted to the Journal of Digital Imaging:
  1. Erdal S, Catalyurek U, Payne P, Kamal J, Saltz J, Gurcan MN, A Knowledge-Anchored Integrative Image Search and Retrieval System, Journal of Digital Imaging, in print, 2008.

Comments

Post a Comment

Popular posts from this blog

Recent publications

The CIA lab has recently had 4 articles published in PLOS One and the Journal of Urology. Automated Staging Of T1 Bladder Cancer Using Digital Pathologic H&E Images: A Deep Learning approach (Journal of Urology). The paper discusses the need for accurately gauging tumor cell intrusion into Lamina Propria in an effort to substage bladder cancer. It explains how transfer learning in conjunction with Convolutional Neural Networks can be used to accurately identify different bladder layers and then compute the distance between tumor nuclei and Lamina Propria. The article is available here:  https://www.jurology.com/article/S0022-5347(18)41148-2/pdf Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning (PLOS One). This paper examines a proposed methodology to automatically differentiate between NET and non-tumor regions based on images of Ki67 stained biopsies. It also uses transfer learning to exploit a rich set of features ...
6 comments
Read more

Drs. Goceri, Kus, and Senaras Present at OSUMC Research Day

On April 25th, Drs. Goceri, Kus, and Senaras presented their research at the OSUMC Research Day.  Dr. Evgin Goceri presented “Automatic and Robust Segmentation of Liver and Its Vessels from MR Datasets for Pre-Evaluation of Liver Translation” which proposed a robust and fully automated method for segmenting the liver and its vessels from MR images. Dr. Goceri’s study presented a novel approach to reducing processing time by employing binary regularization of the level set function. The fully-automatic segmentation of liver and its vessels with the proposed method was more efficient than manual approach and the other methods in the literature in terms of processing time and accuracy. Dr. Pelin Kus presented “Segmentation and Quantification of Tissue Necrosis in Tuberculosis” which focuses on how the immune system of patients infected with M. tuberculosis responds by using many types of cells including macrophages that form granulomas within the pulmonary tissue. Segmentati...
3 comments
Read more

Computer’s help in wound image analysis

Computers help in wound image analysis CIALAB’s work in collaboration with the OSUMC Wound Center researchers entitled, “ Computerized Segmentation and Measurement of Chronic Wound Images” has been accepted to the journal of Computers in Biology and Medicine (CBM). The objective of this study is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. Further details about the paper can be found at the CBM website: www.computersinbiologyandmedicine.com/article/S0010-4825(15)00064-5/abstract
3 comments
Read more