A systematic review on diabetic retinopathy detection using deep learning techniques

R Vij, S Arora - Archives of Computational Methods in Engineering, 2023 - Springer
Segmentation is an essential requirement to accurately access diabetic retinopathy (DR)
and it becomes extremely time-consuming and challenging to detect manually. As a result …

A review on glaucoma disease detection using computerized techniques

F Abdullah, R Imtiaz, HA Madni, HA Khan… - IEEE …, 2021 - ieeexplore.ieee.org
Glaucoma is an incurable eye disease that leads to slow progressive degeneration of the
retina. It cannot be fully cured, however, its progression can be controlled in case of early …

[HTML][HTML] Dense-PSP-UNet: a neural network for fast inference liver ultrasound segmentation

MY Ansari, Y Yang, PK Meher, SP Dakua - Computers in Biology and …, 2023 - Elsevier
Liver Ultrasound (US) or sonography is popularly used because of its real-time output, low-
cost, ease-of-use, portability, and non-invasive nature. Segmentation of real-time liver US is …

[HTML][HTML] Diabetic retinopathy fundus image classification and lesions localization system using deep learning

WL Alyoubi, MF Abulkhair, WM Shalash - Sensors, 2021 - mdpi.com
Diabetic retinopathy (DR) is a disease resulting from diabetes complications, causing non-
reversible damage to retina blood vessels. DR is a leading cause of blindness if not …

A lightweight robust deep learning model gained high accuracy in classifying a wide range of diabetic retinopathy images

MAK Raiaan, K Fatema, IU Khan, S Azam… - IEEE …, 2023 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is a common complication of diabetes mellitus, and retinal blood
vessel damage can lead to vision loss and blindness if not recognized at an early stage …

Lightweight dense-scale network (LDSNet) for corn leaf disease identification

W Zeng, H Li, G Hu, D Liang - Computers and Electronics in Agriculture, 2022 - Elsevier
The identification of corn leaf diseases in real scenarios faces important challenges, such as
complex background interference, intra-and inter-class scale changes, and lightweight …

Improving automated latent fingerprint detection and segmentation using deep convolutional neural network

M Chhabra, KK Ravulakollu, M Kumar… - Neural Computing and …, 2023 - Springer
Latent fingerprint segmentation is a complex process of separating relevant areas called
fingerprints from an irrelevant background in the latent fingerprint image which is of poor …

A hybrid algorithm to enhance colour retinal fundus images using a Wiener filter and CLAHE

MJ Alwazzan, MA Ismael, AN Ahmed - Journal of Digital Imaging, 2021 - Springer
Digital images used in the field of ophthalmology are among the most important methods for
automatic detection of certain eye diseases. These processes include image enhancement …

Segmentation and classification of breast cancer using novel deep learning architecture

S Ramesh, S Sasikala, S Gomathi, V Geetha… - Neural Computing and …, 2022 - Springer
Breast cancer is one of the most frequent cancers in women, and it has a higher mortality
rate than other cancers. As a result, early detection is critical. In computer-assisted disease …

Effect of image transformation on EfficientNet model for COVID-19 CT image classification

AS Ebenezer, SD Kanmani, M Sivakumar… - Materials Today …, 2022 - Elsevier
Abstract The Novel Corona Virus 2019 has drastically affected millions of people all around
the world and was a huge threat to the human race since its evolution in 2019. Chest CT …