Current Medical Imaging - Volume 16, Issue 6, 2020

Background: Using functional neuroimaging techniques to explore the central mechanism of acupoint specificity, the key of acupuncture theory and clinical practice, has attracted increasing attention worldwide. This review aimed to investigate the current status of functional neuroimaging studies on acupoint specificity and explore the potential influencing factors for the expression of acupoint specificity in neuroimaging stu Read More

Breast cancer is leading cancer among women for the past 60 years. There are no effective mechanisms for completely preventing breast cancer. Rather it can be detected at its earlier stages so that unnecessary biopsy can be reduced. Although there are several imaging modalities available for capturing the abnormalities in breasts, mammography is the most commonly used technique, because of its low cost. Computer-Aid Read More

Background: Image reconstruction is the mathematical process which converts the signals obtained from the scanning machine into an image. The reconstructed image plays a fundamental role in the planning of surgery and research in the medical field. Discussion: This paper introduces the first comprehensive survey of the literature about medical image reconstruction related to diseases, presenting a categorical study abo Read More

Background: With the advancement of technology, Computed Tomography (CT) scan imaging can be used to gain deeper insight into the cause of death. Aims: The purpose of this study was to perform a systematic review of the efficacy of Post- Mortem Computed Tomography (PMCT) scan compared with the conventional autopsies gleaned from literature published in English between the year 2009 and 2016. Methodology: Read More

Objective: The aim of our study was to present the prevalence of thyroid nodules we incidentally discovered by routine Magnetic Resonance Imaging (MRI) of the cervical spine, to evaluate their clinical significance, and to discuss the current clinical approach to incidental thyroid nodules. Methods: We retrospectively evaluated the cervical spinal MRI studies of 512 patients. Thyroid glands were evaluated for morphologic a Read More

Objective: The study aimed to investigate the relationship between the corpus callosum area (CCa) and the degree of cerebral atrophy in patients with cerebral atrophy. Methods: 119 patients with brain atrophy were grouped according to the degree of brain atrophy. Median sagittal CCa and intracranial area (ICa) were measured, and the ratio of corpus callosum to the intracranial area (CCa-ICa ratio) was calculated. The data Read More

Purpose: Parkinson's disease (PD), which is the second most common neurodegenerative disease following Alzheimer’s disease, can be diagnosed clinically when about 70% of the dopaminergic neurons are lost and symptoms are noticed. Neuroimaging methods such as single photon emission computed tomography have become useful tools in vivo to assess dopamine transporters (DATs) in the striatal region. However, inter- a Read More

Background: In the United States, prostate cancer has a relatively large impact on men's health. Magnetic resonance imaging (MRI) is useful for the diagnosis and treatment of prostate cancer. Introduction: The purpose of this study was to develop a quantitative marker for use in prostate cancer magnetization transfer (MT) magnetic resonance imaging (MRI) studies that is independent of radiofrequency (RF) saturation amplitude. Read More

Background: Breast cancer is one of the most leading causes of cancer deaths among women. Early detection of cancer increases the survival rate of the affected women. Machine learning approaches that are used for classification of breast cancer usually takes a lot of processing time during the training process. This paper attempts to propose a Machine Learning approach for breast cancer detection in mammograms, which Read More

Background: In this study, a novel and fully automatic skin disease classification approach is proposed using statistical feature extraction and Artificial Neural Network (ANN) based classification using first and second order statistical moments, the entropy of different color channels and texture-based features. Aims: The basic aim of our study is to develop an automated system for skin disease classification that can help Read More

Background: Glioma is one of the most common and aggressive primary brain tumors that endanger human health. Tumors segmentation is a key step in assisting the diagnosis and treatment of cancer disease. However, it is a relatively challenging task to precisely segment tumors considering characteristics of brain tumors and the device noise. Recently, with the breakthrough development of deep learning, brain tumor segme Read More

Background: Metaplastic breast cancer (MC) is a rare disease, thus it is difficult to study its clinical outcomes. Objectives: To investigate whether any clinicopathological or imaging features were associated with clinical outcome in MC. Methods: We retrospectively evaluated the clinicopathological and imaging findings, and the clinical outcomes of seventy-two pathologically confirmed MCs. We then compared these parameters bet Read More

Background: Ultrasound (US) imaging can be a convenient and reliable substitute for magnetic resonance imaging in the investigation or screening of articular cartilage injury. However, US images suffer from two main impediments, i.e., low contrast ratio and presence of speckle noise. Aims: A variation of anisotropic diffusion is proposed that can reduce speckle noise without compromising the image quality of the edges and ot Read More

Background and Objective: In order to reduce time complexity and to improve the computational efficiency in diagnosing process, automated brain tissue segmentation for magnetic resonance brain images is proposed in this paper. Methods: This method incorporates two processes, the first one is preprocessing and the second one is segmentation of brain tissue using Histogram based Swarm Optimization techniques. The pr Read More

Background: Hyperechoic breast lesions are a rare group of breast masses in routine practice. Most of these lesions are benign. However, they rarely may be malignant. Hyperechoic lesions can be evaluated using the same criteria for malignant lesions. Clinical history, mammographic appearance, and certain sonographic features (non-circumscribed margins, irregular shape, presence of hypoechoic areas, nonparallel Read More