Skip to main content

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. Segmentation and quantification of the necrosis often formed in the center of the granuloma will enable experts to understand the relationship between genes, molecules, and cells that contribute to granuloma and/or lung necrosis and to better identify and treat patients infected with M. tuberculosis. Dr. Kus’s study developed an algorithm to quantify and delineate necrotic areas from histopathological slides for the tuberculosis disease. The promising results of this study indicate the possibility of using such an algorithm for large scale analysis.

Dr. Caglar Senaras presented “Automated Otoscopy to Diagnose Ear Pathology” which focused on methods for identifying ear infections. His project addressed the need to improve diagnostic accuracy by developing an objective method to assess the eardrum. Objective methods to identify eardrum abnormalities would assist clinicians in diagnosing or ruling out pathologies that may be subtle on clinical otoscopy (e.g., middle ear fluid). In Dr. Senaras’s study, a computer-based image analysis approach was proposed which can objectively determine whether an eardrum is “normal” or “abnormal”.

Comments

  1. Ralph C. KieferMarch 25, 2019 at 1:53 AM

    Writing their gastroenterology fellowship personal statement is the big challenge. If your writing isn’t your strongest suit or if you feel that you will need that extra hand thenread review for tips and suggestion.

    ReplyDelete
  2. AnonymousMarch 25, 2019 at 7:23 PM

    Do you want to write a well and unique Rheumatology Fellowship Personal Statement? Writing should appear to be arduous initially; however with the correct dose of determination, what's arduous becomes simple. And to assist you, here are a unit seven tips that may assist you out follow the link for best Pediatric Rheumatology Fellowship Personal Statement.

    ReplyDelete
  3. AnonymousMarch 25, 2019 at 7:30 PM

    All the medical students try to reach their goal but sometimes they were misguided. Here http://www.medicalresidencyhelp.com/medical-residency-personal-statement-services/pathology-residency-personal-statement-help/ our writers share their knowledge of this specialty and combined with their writing experience. You will find your way to success here.

    ReplyDelete

Post a Comment

Popular posts from this blog

CIALAB encouraging talented young minds with summer internships

CIALAB is pleased to introduce the three interns namely Tong Gan, Rosana Rodriguez Milanes and Michael Priddy working through summer’09. Rosana Rodriguez Milanes - I am a third year undergraduate student in Electronic Engineering from Universidad del Norte, Colombia. My experience as a volunteer foreign student in the Clinical Image Analysis Laboratory has been an edifying, gratifying and enriching. Being able to participate, to learn and to collaborate in the Clinical Image Analysis Laboratory during the past two weeks has allowed me to improve my analytical and interpretative skills in processing histopathological and MRI images. I have been able to learn about segmentation, region growing, splitting and merging algorithms development. I have also had the privilege of knowing and interacting with excellent engineers who have helped me improve my skills as a foreign student. I am grateful for the opportunity that the Ohio State University has given me to collaborate and to learn with
1 comment
Read more

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 developed
6 comments
Read more