Medico-visual processing is a rapidly expanding and significant field right now. A number of
modules, including X-ray, ultrasound, MRI, CAT, PET, SPECT, and BIOPSY, are used to get …

Telah berhasil dilakukan klasifikasi kanker paru-paru dari 120 data citra CT Scan. Pada
penelitian, proses preposisi dimulai dengan variasi filtering menggunakan low pass filter …

A Brain tumour is formed by a gradual addition of abnormal cells, and this is one of the major
causes of death among other sorts of cancers. It is necessary to classify brain tumor using …

The current paper proposes a new hierarchical procedure for efficient diagnosis of lung
cancer computed tomography (CT) images. Here, after noise removal based on median …

The main object of the study is to evaluate the correctness parameter of brain MRI images
using KNN compared to SVM. The KNN algorithm has good accuracy in MRI images …

This paper presents two lightweight deep learning models for efficient detection and
segmentation of brain tumors from MRI scans. A custom-made Convolutional Neural …

The study's main objective is to detect brain tumors more precisely in MRI images using
CNN and comparing it to SVM. Materials and Methods: We gathered 40 examples of varied …

Background: In clinical oncology, precise segmentation of the target tumor is essential. The
positron emission tomography (PET)/computed tomography (CT) scanner effectively …

Early detection and classification plays important role in healthcare monitoring system. The
development of automated brain tumor detection and classification techniques using …

This paper presents two lightweight deep learning models for efficient detection and
segmentation of brain tumors from MRI scans. A custom-made Convolutional Neural …