Paper Title

Lung Tumor Segmentation Using U-Net Architecture

Article Identifiers

Registration ID: IJNRD_184999

Published ID: IJNRD2212202

DOI: Click Here to Get

Authors

Madhushree R , Dr. Prabha R , Dr. Asha

Keywords

Lung tumor, U-Net, Convolution Neural Networks.

Abstract

Lung cancer screening based on Low-Dose CT (LDCT) has broadly implemented for the effectiveness and fast execution. Radiologists who worked with highest LDCT conceal image face for more confrontation, despite tedious labour and robotic repetition, the simple deletion of minor nodules, the absence of uniform criteria, etc. This calls for an appropriate strategy to aid radiologists in raising the observing the Nodule precision for effectiveness, affordability. The novel-based Deep Neural Network Systems have the potential to be used in the approach for detecting lung nodules. However, the successfulness for Hospitalized practice has not successfully recognized. The use for developing and estimate a Deep Learning Algorithm (DL) in Recognizing Pulmonary Nodules (PNs) for LDCT and investigate prevalence of Pulmonary nodules in China. Protocol with Reference Standard and Deep Learning Algorithm for finding Positive Nodules as researches done in Bland-Altman Examination. Lung Nodule Analysis (LUNA) is a Database which was available publically for the outermost Examination. The frequency of NCPNs also instigated and also different information about number, location, characteristics of pulmonary nodules from two radiologists.

How To Cite

"Lung Tumor Segmentation Using U-Net Architecture", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.7, Issue 12, page no.c9-c14, December-2022, Available :https://ijnrd.org/papers/IJNRD2212202.pdf

Issue

Volume 7 Issue 12, December-2022

Pages : c9-c14

Other Publication Details

Paper Reg. ID: IJNRD_184999

Published Paper Id: IJNRD2212202

Downloads: 000121135

Research Area: Engineering

Country: Bangalore, karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2212202.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2212202

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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