Efficient Detection of Brachial Plexus in Ultrasound Images using Machine Learning Algorithms
Deepak Sharma1, Lalit kumar2

1Deepak Sharma*, Research scholar, MD University, Rohtak, India.
2Lalit Gaur, PG student, C-DAC, GGSIP University, New Delhi, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 4195-4203 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1612109119/2019©BEIESP | DOI: 10.35940/ijeat.A1612.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Humans can identify objects from an image. Only better knowledge can help to identify specific objects from the field in which we are working. The present work aims at detection of collection of nerves called the Brachial Plexus in ultrasound images. Ultrasound Images has been used for its low prices and low risks but they poses some challenges to detecting the Brachial Plexus in ultrasound images.
Keywords: Mobile Adhoc Network (MANET), AODV Protocol, Black Hole, cooperative black hole.