Diagnosis of Leptomeningeal Metastases Disease in MRI Images by Using Image Enhancement Methods

Diagnosis of Leptomeningeal Metastases Disease

in MRI Images by Using Image Enhancement

Methods

Mehmet Gül1, Sadık Kara1, Abdurrahman Işıkdoğan2, and Yusuf Yarar3

1Biomedical Engineering Institute, Fatih University, Istanbul

2Hospital of Oncology, Dicle University, Diyarbakır

3Selahaddin’i Eyyubi Hospital, Diyarbakır

 

Abstract: Leptomeningeal Metastases (LM) disease is the advanced stages of some complicated cancers. It Contaminates in the Cerebrospinal Fluid (CSF). Tumors might be in macroscopic or microscopic sizes. The medical operation is more risky than other cancers. Consequently, diagnosis of leptomeningeal metastases is important. Different methods are used to diagnose LM disease such as CSF examination and imaging systems Magnetic Resonance Imaging (MRI) or Computer Tomography (CT) examination. CSF examination result is more accurate compared to CT or MRI imaging systems. However imaging systems’ results are taken more early than CSF examination. Some details in MRI images are hidden and if the proper image enhancement method is used, the details will be revealed. Diagnosis of LM disease can be earlier with accurate results at that time. In this study, some image enhancement methods were used. The probability of result of Logarithmic Transformation (LT) method and Power-Law Transformation (PLT) method were almost the same and result was p=0.000 (p<0.001), and statistically high result was obtained. The probability of Contrast Stretching (CS) method was p=0.031 (p<0.05), and this result was statistically significant. The other four methods’ results were insignificant. These methods are Image Negatives Transformation (INT) method, thresholding transformations method; Gray-Level Slicing (GLS) method and Bit-Plane Slicing (BPS) method.

Keywords: Cerebrospinal Fluid (CSF) examination, Computed Tomography (CT), Image Enhancement methods, Leptomeningeal Metastases, Magnetic Resonance Imaging (MRI).

Received March 23, 2015; accepted August 12, 2015

 

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