Enhanced medical image analysis: leveraging CUDA for fast and accurate Pneumonia detection with optimized CNNs

Enhanced medical image analysis: leveraging CUDA for fast and accurate Pneumonia detection with optimized CNNs

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliografski detalji
Glavni autor:	Alvi, Md.Waseq Alauddin
Daljnji autori:	Alam, Md. Ashraful
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2024
Teme:	Disease detection Pneumonia detection Image analysis Convolutional neural network Healthcare diagnostics CUDA NVIDIA Deep learning Diagnostic imaging > Data processing. Image processing > Digital techniques. Pneumonia. Computational intelligence. Neural networks (Computer science).
Online pristup:	http://hdl.handle.net/10361/24360

Similar Items

Pneumonia Disease detection using the convolutional neural network
od: Ashrafee, Md. Iftid, i dr.
Izdano: (2024)

A comparative analysis of the different CNN-LSTM model caption generation of medical images
od: Amin, Mahzabin Yasmin Binte, i dr.
Izdano: (2023)

Detecting anomalies in human eyes using structural similarity index measurement
od: Jahan, Monwar, i dr.
Izdano: (2019)

Detection of skin cancer using Convolutional neural network
od: Ahsan, Abu Sa-adat Mohamed Moon-Im Al, i dr.
Izdano: (2020)

ResInvolution: an involution-ResNet fused global spatial relation leveraging model for histopathological image analysis under federated learning environment
od: Dipto, Shakib Mahmud
Izdano: (2024)

Traumatic meningeal enhancement detection by deep learning-based biomedical image analysis and handcrafted features extraction
od: Uddin, Mohammad Sakib, i dr.
Izdano: (2024)

Demystify the blackbox model of automated detection of lung and kidney diseases from X-ray and CT radiographs
od: Islam, Md. Nazmul
Izdano: (2023)

Early detection of parkinson’s disease using image processing and artificial neural network
od: Rumman, Mosarrat, i dr.
Izdano: (2018)

Leveraging unsupervised segmentation for semi-supervised renal calculi and carcinoma segmentation and classification
od: Faruk, Farhan, i dr.
Izdano: (2024)

Skin cancer classification for seven types of skin lesions
od: Rahman, Md. Tawsifur, i dr.
Izdano: (2024)

Smoke detection using image processing
od: Sarker, Md. Kamrujjaman
Izdano: (2018)

Comparison of deep transfer learning models for cancer diagnosis
od: Joya, Nadia Islam, i dr.
Izdano: (2023)

Cancer detection using image processing techniques based on cell counting, cell area measurement and clump detection
od: Pavel, Monirul Islam, i dr.
Izdano: (2018)

End to end Bangla handwritten and scene text detection using convolutional neural network
od: Mahal, Somania Nur, i dr.
Izdano: (2018)

Exploring deep features: deeper fully convolutional neural network for image segmentation
od: Kamran, Sharif Amit, i dr.
Izdano: (2017)

Optimization techniques for speedup in a parallel algorithm
od: Faria, Fairuz, i dr.
Izdano: (2018)

A review on carbon nanotube: a new era in cancer diagnosis & therapy
od: Parvez, Safi
Izdano: (2023)

Evaluation of MicrocinE492 gene presence in Klebsiella pneumoniae isolated from clinical samples.
od: Islam, Faria
Izdano: (2019)

Image classification using deep neural network for efficient identification of traffic sign
od: Saha, Sourajit
Izdano: (2018)

A prospective study on the efficiency of ciprofloxacin in combination with chloramphenicol and probiotics against multiple antibiotics resistant Klebsiella pneumoniae
od: Ahmed, Akash
Izdano: (2018)

Utilizing deep learning architectures for early detection of lung diseases in chest X-ray images
od: Ahmed, Sarder Tanvir, i dr.
Izdano: (2024)

Vision Transformer (ViT) approach in computer aided diagnosis of acute lymphoblastic leukemia
od: Amin, Sifatul, i dr.
Izdano: (2023)

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
od: Sagor, Mostofa Kamal, i dr.
Izdano: (2021)

An efficient approach to detect melanoma skin cancer using a custom CNN model
od: Rahman, K.M Saidur, i dr.
Izdano: (2023)

Classification of retinal diseases from OCT images using deep learning models
od: Mokarrom, Md Saif, i dr.
Izdano: (2024)

Fetal plane classification from 2D-ultrasound images leveraging squeeze and excitation self-attention mechanism for feature recalibration in MedMamba
od: Riju, Tanjim Islam, i dr.
Izdano: (2024)

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
od: Tasawar, Ihtyaz Kader, i dr.
Izdano: (2021)

The combined effect of Moxifloxacin and Ciprofloxacin against multidrug-resistant Klebsiella pneumoniae
od: Hossain, Mehrin, i dr.
Izdano: (2022)

Navigational intelligence at river: a laser-based imaging approach for nocturnal vessel detection
od: Zafreen, Zasia, i dr.
Izdano: (2024)

Monitoring of endangered fish using image processing and AI tools
od: Hossain, Naheen, i dr.
Izdano: (2019)

SWT and SIFT based copy-move image forgery detection
od: Das, Taposh, i dr.
Izdano: (2018)

Suspicious human-movement detection
od: Biswas, Amlan, i dr.
Izdano: (2018)

Bacterial etiology and antibiotic resistance pattern of adult pneumonia in South Asia: a review
od: Eusra, Kazi Fatiha, i dr.
Izdano: (2023)

D-ARTNET22 V1: a neural network framework against stolen digital artworks getting Non-Fungible Token (NFT) labels
od: Dipro, Farhan Hasin, i dr.
Izdano: (2024)

In silico drug designing against Klebsiella pneumoniae adhesin protein
od: Hoq, Muntasirul
Izdano: (2019)

Fake currency detection using image processing method
od: Alimushwan, Munshi Md., i dr.
Izdano: (2017)

Deepfake detection using neural networks
od: Sakib, Sadman, i dr.
Izdano: (2021)

Identification and comparative analysis of potholes using image processing algorithms
od: Anik, Fahim Shahriare, i dr.
Izdano: (2018)

Cancer classification using deep learning from medical image data
od: Monir, Raiyan Janik, i dr.
Izdano: (2022)

Single and multi-view 2D image processing for enhanced 3D object reconstruction
od: Ghosh, Swapnil, i dr.
Izdano: (2024)