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Abstract

The liver is a vital organ of the human body and hepatic cancer is one of the major causes of cancer deaths. Early and rapid diagnosis can reduce the mortality rate. It can be achieved through computerized cancer diagnosis and surgery planning systems. Segmentation plays a major role in these systems. This work evaluated the efficacy of the SegNet model in liver and particle swarm optimization-based clustering technique in liver lesion segmentation. Over 2400 CT images were used for training the deep learning network and ten CT datasets for validating the algorithm. The segmentation results were satisfactory. The values for Dice Coefficient and volumetric overlap error achieved were 0.940 ± 0.022 and 0.112 ± 0.038, respectively for liver and the results for lesion delineation were 0.4629 ± 0.287 and 0.6986 ± 0.203, respectively. The proposed method is effective for liver segmentation. However, lesion segmentation needs to be further improved for better accuracy.
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Authors and Affiliations

P Vaidehi Nayantara
1
Surekha Kamath
1
Manjunath KN
2
Rajagopal Kadavigere
2

  1. Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
  2. Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
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Abstract

The 17-4 PH Stainless Steel material is known for its higher strength and, therefore, extensively used to build structures for aerospace, automotive, biomedical, and energy applications. The parts must operate satisfactorily in different environmental conditions to widen the diverse application. The selective laser melting (SLM) technique build parts cost-effectively, ensuring near-net shape manufacturability. Laser power, scan speed, and hatch distance operating at different conditions were used to develop parts and optimize for higher density in printed parts. Laser power, scan speed, and hatch distance resulted in the percent contribution towards density equal to 73.74%, 24.48%, and 1.78%. The optimized conditions resulted in higher density and relative density equal to 7.76 g/cm 3 and 99.48%. Printed parts' corrosion rate and wear loss showed more stability in NaCl corrosive medium even at 75 °C than 1M of HCL corrosive medium. Less pitting corrosion was observed on the samples treated in NaCl solution at 25 °C and 75 °C at 72 Hrs than in HCL solution. Therefore, 17-4 PH SS parts are best suited even in marine applications.
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Authors and Affiliations

Priya Sahadevan
1
Chithirai Pon Selvan
2
ORCID: ORCID
G C Manjunath Patel
3
ORCID: ORCID
Amiya Bhaumik
1

  1. Lincoln University College Selangor, Malaysia
  2. Curtin University Dubai, United Arab Emirates
  3. PES Institute of Technology and Management, Shivamogga, Visvesvaraya Technological University, Belagavi, India
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Abstract

The versatile application of titanium alloy in the aerospace industry and it’s hard to machine characteristics focus towards the additive manufacturing. The Ti-6Al-4V alloy is manufactured using the electron beam source with a novel method of prepositioned titanium alloy wires. The tribology of the additive manufactured titanium alloy under dry sliding condition is experimented and analysed using Taguchi technique. The targeted objective of minimum tribological responses are attained with the identified optimal parameters as load – 9.81 N, sliding velocity – 3 m/s, sliding distance – 3000 m for minimum specific wear rate and load – 9.81 N, sliding velocity – 3 m/s, sliding distance – 1000 m for minimum coefficient of friction. Among the parameters tested, load is found to be the dominant factor on the tribology of additively manufactured titanium alloy. The morphological analysis on the worn surface and debris revealed the existence of abrasion, delamination and adhesion wear mechanisms. The increase in the load dominantly showed the appearance of delamination mechanism.
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Authors and Affiliations

A. Manjunath
1
ORCID: ORCID
V. Anandakrishnan
2
ORCID: ORCID
S. Ramachandra
1
ORCID: ORCID
K. Parthiban
1
ORCID: ORCID
S. Sathish
3
ORCID: ORCID

  1. Gas Turbine Research Establishment, Defence Research & Development Organization, Bangalore, Karnataka-560093, India
  2. Department of Production Engineering, National Institute of Technology Tiruchirapalli, Tiruchirappalli – 620015, Tamil Nadu, India
  3. Department of Mechatronics Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Namakkal – 637215, Tamil Nadu, India

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