A novel deep learning model for breast lesion classification using ultrasound Images: A multicenter data evaluation
Purpose Breast cancer is one of the major reasons of death due to cancer in women. Early
diagnosis is the most critical key for disease screening, control, and reducing mortality. A …
diagnosis is the most critical key for disease screening, control, and reducing mortality. A …
Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs
The dynamic contrast-enhanced MR imaging plays a crucial role in evaluating the
effectiveness of neoadjuvant chemotherapy (NAC) even since its early stage through the …
effectiveness of neoadjuvant chemotherapy (NAC) even since its early stage through the …
Early prediction of breast cancer recurrence for patients treated with neoadjuvant chemotherapy: a transfer learning approach on DCE-MRIs
Simple Summary An early prediction of Breast Cancer Recurrence (BCR) for patients
undergoing neoadjuvant chemotherapy (NACT) could better guide clinicians in the …
undergoing neoadjuvant chemotherapy (NACT) could better guide clinicians in the …
A completely automated CAD system for mass detection in a large mammographic database
Mass localization plays a crucial role in computer‐aided detection (CAD) systems for the
classification of suspicious regions in mammograms. In this article we present a completely …
classification of suspicious regions in mammograms. In this article we present a completely …
Automatic lung segmentation in CT images with accurate handling of the hilar region
G De Nunzio, E Tommasi, A Agrusti, R Cataldo… - Journal of digital …, 2011 - Springer
A fully automated and three-dimensional (3D) segmentation method for the identification of
the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is …
the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is …
Robustness evaluation of a deep learning model on sagittal and axial breast DCE-MRIs to predict pathological complete response to neoadjuvant chemotherapy
To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-
Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as …
Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as …
Feature selection and classification in mammography using hybrid crow search algorithm with Harris hawks optimization
S Thawkar - Biocybernetics and Biomedical Engineering, 2022 - Elsevier
The purpose of this study is to develop a hybrid algorithm for feature selection and
classification of masses in digital mammograms based on the Crow search algorithm (CSA) …
classification of masses in digital mammograms based on the Crow search algorithm (CSA) …
[PDF][PDF] A review on computer aided detection and diagnosis of lung cancer nodules
SS Parveen, C Kavitha - International Journal of Computers & Technology, 2012 - Citeseer
In this paper, a attempt has been made to summarize some of the information about CAD
and CADx for the purpose of early detection and diagnosis of lung cancer. Computer Aided …
and CADx for the purpose of early detection and diagnosis of lung cancer. Computer Aided …
Contrast-enhanced mammography (CEM) capability to distinguish molecular breast cancer subtypes
E Luczynska, T Piegza, J Szpor, S Heinze, T Popiela… - Biomedicines, 2022 - mdpi.com
With breast cancer ranking first among the most common malignant neoplasms in the world,
new techniques of early detection are in even more demand than before. Our awareness of …
new techniques of early detection are in even more demand than before. Our awareness of …
Breast cancer: A hybrid method for feature selection and classification in digital mammography
In this article, a hybrid approach based on the Whale optimization algorithm (WOA) and the
Dragonfly algorithm (DA) is proposed for breast cancer diagnosis. The hybrid WOADA …
Dragonfly algorithm (DA) is proposed for breast cancer diagnosis. The hybrid WOADA …