A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Ensemble deep-learning-enabled clinical decision support system for breast cancer diagnosis and classification on ultrasound images
Simple Summary In the literature, there exist plenty of research works focused on the
detection and classification of breast cancer. However, only a few works have focused on …
detection and classification of breast cancer. However, only a few works have focused on …
Dual encoder–decoder-based deep polyp segmentation network for colonoscopy images
J Lewis, YJ Cha, J Kim - Scientific Reports, 2023 - nature.com
Detection of colorectal polyps through colonoscopy is an essential practice in prevention of
colorectal cancers. However, the method itself is labor intensive and is subject to human …
colorectal cancers. However, the method itself is labor intensive and is subject to human …
AAU-net: an adaptive attention U-net for breast lesions segmentation in ultrasound images
Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …
ultrasound images. However, similar intensity distributions, variable tumor morphologies …
SMU-Net: Saliency-guided morphology-aware U-Net for breast lesion segmentation in ultrasound image
Z Ning, S Zhong, Q Feng, W Chen… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Deep learning methods, especially convolutional neural networks, have been successfully
applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern …
applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern …
A novel chaos-based privacy-preserving deep learning model for cancer diagnosis
Early cancer identification is regarded as a challenging problem in cancer prevention for the
healthcare community. In addition, ensuring privacy-preserving healthcare data becomes …
healthcare community. In addition, ensuring privacy-preserving healthcare data becomes …
Breast cancer detection using an ensemble deep learning method
In this work, the effectiveness of the deep learning model is applied for one-dimensional
data when converted to images. This work is based on the effective conversion of one …
data when converted to images. This work is based on the effective conversion of one …
Rethinking the unpretentious U-net for medical ultrasound image segmentation
Breast tumor segmentation from ultrasound images is one of the key steps that help us
characterize and localize tumor regions. However, variable tumor morphology, blurred …
characterize and localize tumor regions. However, variable tumor morphology, blurred …
[HTML][HTML] IEViT: An enhanced vision transformer architecture for chest X-ray image classification
Abstract Background and Objective: Chest X-ray imaging is a relatively cheap and
accessible diagnostic tool that can assist in the diagnosis of various conditions, including …
accessible diagnostic tool that can assist in the diagnosis of various conditions, including …