Brain tumor segmentation from MRI images using convolutional neural networks

Brain tumor segmentation from MRI images using convolutional neural networks

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Xehetasun bibliografikoak
Egile nagusia:	Khan, Mushfiqur Rahman
Beste egile batzuk:	Khondaker, Arnisha
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Bain tumor Convolutional Neural Network U-Net ResNet50 ResNext50 EfficientNetB7 Segmentation MRI image Neural networks (Computer science) Image processing > Digital techniques.
Sarrera elektronikoa:	http://hdl.handle.net/10361/24177

Antzeko izenburuak

Detecting brain tumor using deep neural networks from MRI images
nork: Imamuzzaman, A.S.M., et al.
Argitaratua: (2021)

An Efficient deep learning approach to detect Brain Tumor using MRI images
nork: Islam, Annur Tasnim, et al.
Argitaratua: (2022)

An Analysis on Bengali handwritten conjunct character recognition and prediction
nork: Munawar, Maazin, et al.
Argitaratua: (2021)

Unmasking malignancy of lung nodule using a modernized ConvNet toward the design of a vision transformer
nork: Reza, Jamil Ur, et al.
Argitaratua: (2023)

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
nork: Awwal, Alvina, et al.
Argitaratua: (2021)

Bone age comparison using convolutional neural network
nork: Nawaz, Fariha, et al.
Argitaratua: (2019)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
nork: Rahman, Afridi Ibn, et al.
Argitaratua: (2022)

CancerCare: A reliable and secured self-supervising and interactive system using deep learning
nork: Khisa, Pushpakali, et al.
Argitaratua: (2024)

Semantic segmentation of tumor from 3D Structural MRI using U-Net Autoencoder
nork: Farzana, Maisha, et al.
Argitaratua: (2021)

Citrus leaf disease detection by image processing
nork: Chowdhury, Mahir Faisal, et al.
Argitaratua: (2024)

Covid-19 infected lung detection using machine learning
nork: Islam, Md. Muntaha, et al.
Argitaratua: (2022)

Speech command classification based on deep neural networks
nork: Hossain, Md. Sakib, et al.
Argitaratua: (2023)

Tomato leaf disease detection using convolutional neural network
nork: Hasan, Md. Riazul, et al.
Argitaratua: (2023)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
nork: Haque, Samiha, et al.
Argitaratua: (2021)

Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
nork: Choudhury, Prionto Kumar, et al.
Argitaratua: (2024)

Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing
nork: Tasnim, Sadia, et al.
Argitaratua: (2023)

Pyramid pooling enhanced ResUNet for accurate 3D brain image segmentation
nork: Mollah, Md. Shawon, et al.
Argitaratua: (2024)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
nork: Hossain, Mohammad Sakib, et al.
Argitaratua: (2023)

A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI
nork: Akhter, Nasrin
Argitaratua: (2023)

Approaching transfer learning to identify correctly worn facial masks
nork: Sadid, Tausif, et al.
Argitaratua: (2021)

Plant disease detection using convolutional neural network
nork: Hossain, Mohammad Shifat, et al.
Argitaratua: (2021)

Brain tumor detection with convolutional neural network
nork: Galib, Abrar Tahmid, et al.
Argitaratua: (2024)

Skin cancer classification for seven types of skin lesions
nork: Rahman, Md. Tawsifur, et al.
Argitaratua: (2024)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
nork: Ismail, Sayem Mohammad, et al.
Argitaratua: (2021)

Analyzing students’ concentration in online courses through Webcam
nork: Asif, Md., et al.
Argitaratua: (2024)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
nork: Khan, Farhan Sakib, et al.
Argitaratua: (2022)

Early prediction of Alzheimer's disease using convolutional neural network
nork: Abed, Mahjabeen Tamanna, et al.
Argitaratua: (2020)

Classification of different magnetic structures from image data using deep neural networks
nork: Ibn Hasib, Fahad, et al.
Argitaratua: (2023)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
nork: Sharma, Tanmoyee, et al.
Argitaratua: (2021)

Exploring deep features: deeper fully convolutional neural network for image segmentation
nork: Kamran, Sharif Amit, et al.
Argitaratua: (2017)

Semantic segmentation with attention dense U-net for lung extraction from X-ray images
nork: Auvy, Akib Al Mahmud, et al.
Argitaratua: (2023)

Leveraging robust CNN architectures for real-time object recognition from conveyor belt
nork: Moon, Nowrin Tasnim, et al.
Argitaratua: (2023)

An interpretable deep learning approach to detect Alzheimer using MRI images
nork: Oni, Farhan Anzum, et al.
Argitaratua: (2023)

Detection of coronary artery blockage at an early stage using effective deep learning technique
nork: Promit, Tahmid Ashrafee, et al.
Argitaratua: (2023)

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
nork: Athina, Fahima Hasan, et al.
Argitaratua: (2022)

FoodieCal: a convolutional neural network based food detection and calorie estimation system
nork: Mashraf, Chowdhury Zerif, et al.
Argitaratua: (2021)

A decentralized learning-based approach to classify colorectal cancer using Deep Learning Leveraging XAI
nork: Mubin, Kazi Ehsanul, et al.
Argitaratua: (2022)

Tomato leaf disease detection using Resnet-50 and MobileNet Architecture
nork: Tahamid, Abu
Argitaratua: (2021)

Retinal Diseases Detection using Deep Learning
nork: Mashfi, Shahriar, et al.
Argitaratua: (2023)

Skin lesion classification using different CNN models
nork: Oli, Md. Yahea Sultan
Argitaratua: (2023)