AIMC Topic: Biopsy
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Classification of subtypes including LCNEC in lung cancer biopsy slides using convolutional neural network from scratch.
Scientific reports
Feb 3, 2022
Identifying the lung carcinoma subtype in small biopsy specimens is an important part of determining a suitable treatment plan but is often challenging without the help of special and/or immunohistochemical stains. Pathology image analysis that tackl...
Frameless robot-assisted stereotactic biopsies for lesions of the brainstem-a series of 103 consecutive biopsies.
Journal of neuro-oncology
Jan 27, 2022
PURPOSE: Targeted treatment for brainstem lesions requires above all a precise histopathological and molecular diagnosis. In the current technological era, robot-assisted stereotactic biopsies represent an accurate and safe procedure for tissue diagn...
A deep learning model for breast ductal carcinoma in situ classification in whole slide images.
Virchows Archiv : an international journal of pathology
Jan 25, 2022
The pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of pivotal importance for determining optimum cancer treatment(s) and clinical outcomes. Since conventional diagnosis by pat...
[The first data challenge of the french society of pathology: An international competition in 2020, a research tool in A.I. for the future?].
Annales de pathologie
Jan 7, 2022
The french society of pathology (SFP) organized in 2020 its first data challenge with the help of Health Data Hub (HDH). The organisation of this event first consisted in recruiting almost 5000 slides of uterus cervical biopsies obtained in 20 pathol...
Quantifying the cell morphology and predicting biological behavior of signet ring cell carcinoma using deep learning.
Scientific reports
Jan 7, 2022
Signet ring cell carcinoma (SRCC) is a malignant tumor of the digestive system. This tumor has long been considered to be poorly differentiated and highly invasive because it has a higher rate of metastasis than well-differentiated adenocarcinoma. Bu...
AI-based carcinoma detection and classification using histopathological images: A systematic review.
Computers in biology and medicine
Jan 5, 2022
Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell carcinoma and adenocarcinoma are two major subtypes of carcinoma, diagnosed b...
Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.
The Journal of pathology
Dec 28, 2021
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...
Reproducibility of Results
Image Interpretation, Computer-Assisted
Predictive Value of Tests
Risk Assessment
Humans
Proof of Concept Study
Neoplasm Staging
Biopsy
Retrospective Studies
Microscopy
Risk Factors
Colorectal Neoplasms
Lymphatic Metastasis
Early Detection of Cancer
Adipose Tissue
Diagnosis, Computer-Assisted
Deep Learning
Lymph Nodes
Pushing the boundaries of accuracy and reliability during stereotactic procedures: A prospective study on 526 biopsies comparing the frameless robotic and Image-Guided Surgery systems.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Dec 18, 2021
INTRODUCTION: A 12-year long, prospective, single center study was conducted, comparing two frameless systems for brain biopsies: ROSA robotic-assisted stereotaxy and BrainLab Varioguide image-guided stereotaxy (Image Guided Surgery, IGS).
Prostate Cancer: Early Detection and Assessing Clinical Risk Using Deep Machine Learning of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.
Frontiers in immunology
Dec 16, 2021
Detecting the presence of prostate cancer (PCa) and distinguishing low- or intermediate-risk disease from high-risk disease early, and without the need for potentially unnecessary invasive biopsies remains a significant clinical challenge. The aim of...
Optimizing the transfer-learning with pretrained deep convolutional neural networks for first stage breast tumor diagnosis using breast ultrasound visual images.
Microscopy research and technique
Dec 15, 2021
Female accounts for approximately 50% of the total population worldwide and many of them had breast cancer. Computer-aided diagnosis frameworks could reduce the number of needless biopsies and the workload of radiologists. This research aims to detec...
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