Advanced Image Processing in Support of THz Imaging for Early Detection of Gastric Cancer

Author(s):  
Ciobanu Romeo Cristian ◽  
Schreiner Oliver ◽  
Lucanu Nicolae ◽  
Drug Vasile ◽  
Irina Ciortescu ◽  
...  
2001 ◽  
Vol 120 (5) ◽  
pp. A606-A606
Author(s):  
Y MORII ◽  
T YOSHIDA ◽  
T MATSUMATA ◽  
T ARITA ◽  
K SHIMODA ◽  
...  

Author(s):  
A. Sivasangari ◽  
G. Sasikumar

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.


2018 ◽  
Vol 18 (1) ◽  
pp. 82 ◽  
Author(s):  
Jie-Hyun Kim ◽  
Sung Soo Kim ◽  
Jeong Hoon Lee ◽  
Da Hyun Jung ◽  
Dae Young Cheung ◽  
...  

2016 ◽  
Vol 150 (4) ◽  
pp. S871
Author(s):  
Hiroyuki Yamamoto ◽  
Yoshihito Yoshida ◽  
Ryo Morita ◽  
Ritsuko Oikawa ◽  
Tadateru Maehata ◽  
...  

2017 ◽  
Vol 20 (K3) ◽  
pp. 31-37
Author(s):  
Tien Van Tran ◽  
Cat Ngoc Phuong Phan ◽  
Linh Quang Huynh ◽  
Quynh Ngoc Nguyen ◽  
Hieu Trung Nguyen

Cervical pathologies are frequently occuring diseases and may affect women’s quality of life in many ways. These pathologies are curable with early detection and with a following suitable treatment plans. Colposcopy is a standard examination among screening methods which are used to early detect the abnormal lesions on cervix’s surface. Recently, studies about processing polarized image show ability to support diagnosis of the cervix. In this research, we use cervix’s polarized images and image processing algorithms to segment the blood distribution of Nabothian cyst and Trichomonas vaginalis infection. These results have the potential to provide underlying information of the cervix to support the diagnosis.


2021 ◽  
Vol 11 ◽  
Author(s):  
Ruoyue Tan ◽  
Guanghui Zhang ◽  
Ruochen Liu ◽  
Jianbing Hou ◽  
Zhen Dong ◽  
...  

Stomach adenocarcinoma (STAD) is a leading cause of cancer deaths, and the outcome of the patients remains dismal for the lack of effective biomarkers of early detection. Recent studies have elucidated the landscape of genomic alterations of gastric cancer and reveal some biomarkers of advanced-stage gastric cancer, however, information about early-stage biomarkers is limited. Here, we adopt Weighted Gene Co-expression Network Analysis (WGCNA) to screen potential biomarkers for early-stage STAD using RNA-Seq and clinical data from TCGA database. We find six gene clusters (or modules) are significantly correlated with the stage-I STADs. Among these, five hub genes, i.e., MS4A1, THBS2, VCAN, PDGFRB, and KCNA3 are identified and significantly de-regulated in the stage-I STADs compared with the normal stomach gland tissues, which suggests they can serve as potential early diagnostic biomarkers. Moreover, we show that high expression of VCAN and PDGFRB is associated with poor prognosis of STAD. VCAN encodes a large chondroitin sulfate proteoglycan that is the main component of the extracellular matrix, and PDGFRB encodes a cell surface tyrosine kinase receptor for members of the platelet-derived growth factor (PDGF) family. Consistently, Gene Ontology (GO) analysis of differentially expressed genes in the STADs indicates terms associated with extracellular matrix and receptor ligand activity are significantly enriched. Protein-protein network interaction analysis (PPI) and Gene Set Enrichment Analysis (GSEA) further support the core role of VCAN and PDGFRB in the tumorigenesis. Collectively, our study identifies the potential biomarkers for early detection and prognosis of STAD.


Author(s):  
Jiro Watari ◽  
Kentaro Moriichi ◽  
Hiroki Tanabe ◽  
Mikihiro Fujiya ◽  
Hiroto Miwa ◽  
...  

2018 ◽  
Vol 7 (2) ◽  
pp. 687
Author(s):  
R. Lavanya ◽  
G. K. Rajini ◽  
G. Vidhya Sagar

Retinal Vessel detection for retinal images play crucial role in medical field for proper diagnosis and treatment of various diseases like diabetic retinopathy, hypertensive retinopathy etc. This paper deals with image processing techniques for automatic analysis of blood vessel detection of fundus retinal image using MATLAB tool. This approach uses intensity information and local phase based enhancement filter techniques and morphological operators to provide better accuracy.Objective: The effect of diabetes on the eye is called Diabetic Retinopathy. At the early stages of the disease, blood vessels in the retina become weakened and leak, forming small hemorrhages. As the disease progress, blood vessels may block, and sometimes leads to permanent vision loss. To help Clinicians in diagnosis of diabetic retinopathy in retinal images with an early detection of abnormalities with automated tools.Methods: Fundus photography is an imaging technology used to capture retinal images in diabetic patient through fundus camera. Adaptive Thresholding is used as pre-processing techniques to increase the contrast, and filters are applied to enhance the image quality. Morphological processing is used to detect the shape of blood vessels as they are nonlinear in nature.Results: Image features like, Mean and Standard deviation and entropy, for textural analysis of image with Gray Level Co-occurrence Matrix features like contrast and Energy are calculated for detected vessels.Conclusion: In diabetic patients eyes are affected severely compared to other organs. Early detection of vessel structure in retinal images with computer assisted tools may assist Clinicians for proper diagnosis and pathology. 


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