AIMC Topic: Lymph Nodes

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Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Previous studies have explored the potential on radiomics features of primary breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of deep learning (DL) to identify ALN metastasis remains unclear.

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

BioMed research international
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...

Number of lymph nodes dissected and upstaging rate of the N factor in robot-assisted thoracic surgery versus video-assisted thoracic surgery for patients with cN0 primary lung cancer.

Surgery today
PURPOSE: The accuracy of lymph node (LN) dissection in robotic surgery for lung cancer remains controversial. We compared the accuracy of LN dissection in robot-assisted thoracic surgery (RATS) vs. video-assisted thoracic surgery (VATS).

Preclinical feasibility of robot-assisted sentinel lymph node biopsy using multi-modality magnetic and fluorescence guidance in the head and neck.

Head & neck
BACKGROUND: Sentinel lymph node biopsy (SLNB) is a staging procedure dependent on accurate mapping of draining lymphatics via tracers. Robot-assisted SLNB enables access to multiple neck levels with a single incision and intraoperative fluorescence g...

Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer.

Cancer research and treatment
PURPOSE: Assessing the metastasis status of the sentinel lymph nodes (SLNs) for hematoxylin and eosin-stained frozen tissue sections by pathologists is an essential but tedious and time-consuming task that contributes to accurate breast cancer stagin...

Initial experience of a deep learning application for the differentiation of Kikuchi-Fujimoto's disease from tuberculous lymphadenitis on neck CECT.

Scientific reports
Neck contrast-enhanced CT (CECT) is a routine tool used to evaluate patients with cervical lymphadenopathy. This study aimed to evaluate the ability of convolutional neural networks (CNNs) to classify Kikuchi-Fujimoto's disease (KD) and cervical tube...

Deep Learning Mechanism for Predicting the Axillary Lymph Node Metastasis in Patients with Primary Breast Cancer.

BioMed research international
The second largest cause of mortality worldwide is breast cancer, and it mostly occurs in women. Early diagnosis has improved further treatments and reduced the level of mortality. A unique deep learning algorithm is presented for predicting breast c...

Computed Tomography-Based Deep Learning Nomogram Can Accurately Predict Lymph Node Metastasis in Gastric Cancer.

Digestive diseases and sciences
BACKGROUND: Computed tomography is the most commonly used imaging modality for preoperative assessment of lymph node status, but the reported accuracy is unsatisfactory.