Browsing by Subject "Segmentation"
Now showing items 1-16 of 16
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3D Brain image segmentation using 3D tiled convolution neural networks
(Brac University, 2023-09)Gliomas are the primary brain tumors that are most commonly observed in adult patients and exhibit varying degrees of aggressiveness and prognosis. The accurate identification and diagnosis of Gliomas in surgical procedures ... -
An Analysis on Bengali handwritten conjunct character recognition and prediction
(Brac University, 2021-01)In the very active field of handwriting recognition, a lot of research can be found in the detection of the handwriting of various languages, especially English. However, for languages like Bengali, while they hold some ... -
Automatic brain tumor segmentation using U-ResUNet chain model approach
(Brac University, 2021-09)Identifying brain tumors precisely within the early stage is still a challenging problem for the medical sector consistent with recent research. In a previous research approved by Cancer. Net Editorial Board, it was ... -
Biometric retina identification using artificial approach
(Brac University, 2022-05)In this paper, we considered recognizing 2D retina pictures with a Convolutional Neural Network (CNN) for greater accuracy since retina-based identification is the most secure way of establishing identity and identifying ... -
Brain tumor segmentation from MRI images using convolutional neural networks
(Brac University, 2022)Brain tumors result from the accumulation of abnormal cells inside the brain. The process of brain tumor segmentation plays a vital role in detecting early-stage brain tumors. There are several challenges in the tumor ... -
Customer segmentation using K-means
(Brac University, 2022-05)Sales Maximization is a critical aspect of operating any business. Our thesis aims to help businesses to probe deep into their market reach as we group customers us ing the customer segmentation approach. Our dataset is ... -
Detection and 3D visualization of Brain tumor using deep learning and polynomial interpolation
(Brac University, 2019-04)Among di erent imaging techniques MRI, MRSI and CT scans are some of the widely use techniques to visualize brain structures to point out brain anomalies especially brain tumor. Identi cation of brain tumor accurately ... -
Detection of coronary artery blockage at an early stage using effective deep learning technique
(Brac University, 2022-09-28)A coronary artery blockage is a form of coronary artery disease also known as CAD. It is the most common and frequent disease affecting the human body over the age of 65. CAD is a type of cardiovascular disease that ... -
Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
(BRAC University, 2017)Advancements in computing speed and power have made revolutionary changes in medical science practices and this is no different for cardiology. Such advancements in computer sciences have made the existing medical tests ... -
Leveraging unsupervised segmentation for semi-supervised renal calculi and carcinoma segmentation and classification
(Brac University, 2024-06)Indeed it became crucial to develop an AI-driven system for detecting Renal illnesses spontaneously due to a healthcare issue of Renal failure. The global shortage of nephrologists is the core reason for this. This ... -
Lossless segmentation of Brain Tumors from MRI images using 3D U-Net
(Brac University, 2022-01)2D computer vision and activities related to medical image analysis are remarkably guided with the help of Convolutional Neural networks (CNNs) in recent years. Since a chief portion in the available clinical imaging ... -
A novel approach for detecting and recognizing mathematical symbols
(BRAC University, 2016)Extraction and recognition of mathematical characters and equations for documented images is important for many applications, artificially intelligent systems in particular to store or analyze mathematical data. It is vital ... -
Pyramid pooling enhanced ResUNet for accurate 3D brain image segmentation
(Brac University, 2023-09)"Medical picture segmentation is important for clinical applications because it can offer valuable information on disease identification. With the inclusion of deep learning techniques, the original U-Net and ResUnet ... -
Segmentation based Kidney Tumor Classification using Deep Neural Network
(Brac University, 2022-01)Kidney disease is one of many severe chronic disease that a person can have. Early detection of this disease can be pivotal for proper treatment. Different neural net works have proven to be useful in disease prediction ... -
Semantic segmentation with attention dense U-net for lung extraction from X-ray images
(Brac University, 2023-03)"In the diverse field of computer science, deep learning and digital image processing plays a vital role in medical image research. With a deep knowledge on hand, we can make a machine understand any medical documentation, ... -
Tomato leaf disease detection using Resnet-50 and MobileNet Architecture
(Brac University, 2020-04)Diseases in Tomato mostly on the leaves affect the reduction of both the standard and quantity of agricultural products. Several diseases such as bacterial spot, early blight, late blight, leaf mold, septoria leaf spot, ...
