Deep learning techniques to diagnose lung cancer

L Wang - Cancers, 2022 - mdpi.com
Simple Summary This study investigates the latest achievements, challenges, and future
research directions of deep learning techniques for lung cancer and pulmonary nodule …

Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET

I Domingues, G Pereira, P Martins, H Duarte… - Artificial Intelligence …, 2020 - Springer
Medical imaging is a rich source of invaluable information necessary for clinical judgements.
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …

Malignancy detection in lung and colon histopathology images using transfer learning with class selective image processing

S Mehmood, TM Ghazal, MA Khan, M Zubair… - IEEE …, 2022 - ieeexplore.ieee.org
Cancer accounts for a huge mortality rate due to its aggressiveness, colossal potential of
metastasis, and heterogeneity (causing resistance against chemotherapy). Lung and colon …

A machine learning approach to diagnosing lung and colon cancer using a deep learning-based classification framework

M Masud, N Sikder, AA Nahid, AK Bairagi, MA AlZain - Sensors, 2021 - mdpi.com
The field of Medicine and Healthcare has attained revolutionary advancements in the last
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …

Recent advancements in deep learning based lung cancer detection: A systematic review

S Dodia, B Annappa, PA Mahesh - Engineering Applications of Artificial …, 2022 - Elsevier
Cancer is considered to be a key cause of substantial fatality and morbidity in the world. A
report from the International Agency for Research on Cancer (IARC) states that 27 million …

A regional adaptive variational PDE model for computed tomography image reconstruction

W Wei, B Zhou, D Połap, M Woźniak - Pattern Recognition, 2019 - Elsevier
Improving CT images by increasing the number of scans, hence increasing the ionizing
radiation dose, can increase the probability of inducing cancer in the patient. Using fewer …

A holistic overview of deep learning approach in medical imaging

R Yousef, G Gupta, N Yousef, M Khari - Multimedia Systems, 2022 - Springer
Medical images are a rich source of invaluable necessary information used by clinicians.
Recent technologies have introduced many advancements for exploiting the most of this …

Fused weighted federated deep extreme machine learning based on intelligent lung cancer disease prediction model for healthcare 5.0

S Abbas, GF Issa, A Fatima, T Abbas… - … Journal of Intelligent …, 2023 - Wiley Online Library
In the era of advancement in information technology and the smart healthcare industry 5.0,
the diagnosis of human diseases is still a challenging task. The accurate prediction of …

Detection and classification of pulmonary nodules using convolutional neural networks: a survey

P Monkam, S Qi, H Ma, W Gao, Y Yao, W Qian - Ieee Access, 2019 - ieeexplore.ieee.org
CT screening has been proven to be effective for diagnosing lung cancer at its early
manifestation in the form of pulmonary nodules, thus decreasing the mortality. However, the …

Adaptive morphology aided 2-pathway convolutional neural network for lung nodule classification

A Halder, S Chatterjee, D Dey - Biomedical Signal Processing and Control, 2022 - Elsevier
Early-stage detection and identification of malignant pulmonary nodules can allow proper
medication and increase the survival rate of lung cancer patients. High-Resolution …