A.WCFS-IBMDNT

Many recent studies have attempted to define the characteristics of brain tumors to diagnose the illnesses. However, with a large dataset, the correlations across brain tumor characteristics limit the illness diagnosis performance. Furthermore, when using standard approaches for categorization, misclassification outcomes might arise. The WCFS-IBMDNL approach employs the IBMDNN classifier after selecting a subset of characteristics for efficient brain tumor diagnosis with low time complexity. The most significant diagnostic approach used to diagnose brain tumors is Weighted Co-relation Feature Selection Based Iterative Bayesian Multivariate Deep Neural Learning (WCFS-IBMDNT). The WCFS-IBMDNT approach was created to enhance brain tumor diagnosis by requiring the least amount of time [59]. The major importance of WCFS-IBMDNT are as follows:


MRI is the most important technique for the diagnosis of brain tumors. MRI is used in the biomedical to detect and visualize finer details in the internal structure of the body. This technique is used to detect the differences in the tissues. MRI is fundamentally better than CT scanning [60]. This study proposes the computerassisted computed organization feature extraction with abnormal MRI images of brain tumors to develop the accuracy of classification results according to the original feature classification. The initial input database images are fed for preprocessing and the images are transferred as 3 3 blocks. Then for each image of 3 3 blocks, 22 number of texture feature was extracted. Then the extracted feature was used to classify the brain tumor as normal as unusual [61].

The most prevalent metabolites of the brain, such as N-acetyl aspartate (NAA), choline (Cho), creatine (Cr), lipid, and lactate, may be quantified using MR spectroscopy (MRS) [57]. Choline is considered to correspond with cell turnover, therefore variations in Cho might be linked to the stage of radionecrosis. Cho rises in the first few months following radiation therapy, according to two studies, but it declines as radionecrosis develops, according to Rock et al. Rapid Cho, on the other hand, is a common characteristic of tumor recurrence due to high cell turnover [62].

C. CT Scanning (computer tomography)

Computer tomography has a high accuracy than magnetic resonance imaging MRI. CT uses ionizing radiation for the diagnosis of brain tumors. This is used for the diagnosis of primary glaucoma and lymphoma of the Central Nervous System (CNS) was performed [59]. A CT scan may reveal hypodensity in the white matter, as well as a mass effect on surrounding structures. In vascular metastases, localized bleeding may be observed [63].

D.Fused MRI and CT Analysis

Tumor identification is done using a combination of computed tomography CT and MRI scans. Multiple modalities such as CT and MRI are utilized to create the merged pictures (MRI). CT pictures, which are utilized to determine the difference in tissue density, and MRI images, which give a good contrast between distinct bodily tissues, play a vital role in medical image processing [64]. CT pictures show differences in tissue density based on the tissues' capacity to respond to X-rays, whereas MRI images show the contrast between soft tissues. When compared to the source pictures, the fused image retains the complementary and redundant information from both source images, including tumor size and position, allowing for better tumor detection [65].

E. Positron emission tomography [PET]

The brain's major energy source is aerobic glucose metabolism. The most commonly used PET radiotracer, F18-FDG, is actively transported across the BBB and accumulates in areas where aerobic glucose metabolism is enhanced. FDG accumulation is proportional to glucose metabolism in the cell, and higher accumulation correlates to higher cellular metabolism. The brain's typical strong metabolic activity causes high uptake in the normal brain parenchyma, resulting in poor tumor-to-brain contrast. Another possible stumbling block is the nonspecific nature of FDG absorption, which may be seen in inflammatory and infectious processes [66].

PET radiolabelled amino acids increase proportionately to cellular proliferation due to enhanced transport. Tumors increase transporter activity, metabolic enzyme activity, and demand, resulting in increased radiotracer accumulation proportionate to protein synthesis and food demand [67].

F. Single-photon emission computed tomography [SPECT]

SPECT is a low-cost imaging technique that is readily available and may be used in conjunction with CT and MRI to evaluate tumors and RN. In the posttreatment context, a variety of SPECT radiotracers are available for brain tumor imaging. Thallium201 is very accurate for post-treatment evaluation of tumor burden because it concentrates on living tumors; nevertheless, Thallium201 has nonspecific absorption in non-neoplastic processes such as granulomatous or fungal etiologies [66].

Thallium201 absorption is unaffected by the BBB and is primarily determined by the pace of cell growth, making it highly selective for brain tumors. Thallium201- SPECT had a sensitivity of 71.7 percent and a specificity of 80.9 percent for supratentorial brain tumors, according to a retrospective analysis of 90 patients. Because tumor growth rates are substantially greater than normal brain parenchyma, thalllium201 accumulates in brain malignancies without considerable absorption in the normal brain parenchyma, producing good tumor-to-background contrast [68, 69].
