Live Updates: COVID-19 Cases
  • World 18,978,366
    World
    Confirmed: 18,978,366
    Active: 6,098,603
    Recovered: 12,168,522
    Death: 711,241
  • USA 4,973,568
    USA
    Confirmed: 4,973,568
    Active: 2,271,830
    Recovered: 2,540,137
    Death: 161,601
  • Brazil 2,862,761
    Brazil
    Confirmed: 2,862,761
    Active: 744,706
    Recovered: 2,020,637
    Death: 97,418
  • India 1,964,536
    India
    Confirmed: 1,964,536
    Active: 595,461
    Recovered: 1,328,336
    Death: 40,739
  • Russia 866,627
    Russia
    Confirmed: 866,627
    Active: 183,111
    Recovered: 669,026
    Death: 14,490
  • South Africa 529,877
    South Africa
    Confirmed: 529,877
    Active: 143,313
    Recovered: 377,266
    Death: 9,298
  • Mexico 456,100
    Mexico
    Confirmed: 456,100
    Active: 101,694
    Recovered: 304,708
    Death: 49,698
  • Peru 447,624
    Peru
    Confirmed: 447,624
    Active: 120,966
    Recovered: 306,430
    Death: 20,228
  • Chile 364,723
    Chile
    Confirmed: 364,723
    Active: 16,640
    Recovered: 338,291
    Death: 9,792
  • Spain 352,847
    Spain
    Confirmed: 352,847
    Active: 324,348
    Recovered: ?
    Death: 28,499
  • Iran 317,483
    Iran
    Confirmed: 317,483
    Active: 24,749
    Recovered: 274,932
    Death: 17,802
  • UK 307,184
    UK
    Confirmed: 307,184
    Active: 260,820
    Recovered: ?
    Death: 46,364
  • Saudi Arabia 282,824
    Saudi Arabia
    Confirmed: 282,824
    Active: 34,490
    Recovered: 245,314
    Death: 3,020
  • Pakistan 281,863
    Pakistan
    Confirmed: 281,863
    Active: 19,770
    Recovered: 256,058
    Death: 6,035
  • Italy 248,803
    Italy
    Confirmed: 248,803
    Active: 12,646
    Recovered: 200,976
    Death: 35,181
  • Bangladesh 246,674
    Bangladesh
    Confirmed: 246,674
    Active: 101,657
    Recovered: 141,750
    Death: 3,267
  • Turkey 236,112
    Turkey
    Confirmed: 236,112
    Active: 10,822
    Recovered: 219,506
    Death: 5,784
  • Germany 214,104
    Germany
    Confirmed: 214,104
    Active: 8,759
    Recovered: 196,100
    Death: 9,245
  • France 194,029
    France
    Confirmed: 194,029
    Active: 81,558
    Recovered: 82,166
    Death: 30,305
  • Canada 118,187
    Canada
    Confirmed: 118,187
    Active: 6,437
    Recovered: 102,788
    Death: 8,962
  • China 84,528
    China
    Confirmed: 84,528
    Active: 837
    Recovered: 79,057
    Death: 4,634
  • Netherlands 56,381
    Netherlands
    Confirmed: 56,381
    Active: 50,228
    Recovered: ?
    Death: 6,153
  • Australia 19,890
    Australia
    Confirmed: 19,890
    Active: 8,694
    Recovered: 10,941
    Death: 255
  • S. Korea 14,499
    S. Korea
    Confirmed: 14,499
    Active: 696
    Recovered: 13,501
    Death: 302
  • New Zealand 1,569
    New Zealand
    Confirmed: 1,569
    Active: 23
    Recovered: 1,524
    Death: 22

Deep learning contouring to benefit target-specific Radiation Therapy

Radiation Therapy

Makeup lovers might only know to contour as a way of highlighting facial features, but a technique by the same name is used to determine extremely precise radiation therapy treatment. Once the doctors have identified the size and shape of the tumor in diagrammatic detail, contouring helps them design specific target volumes for radiation therapy.

This idea of deep learning to improve the extremely time-taking, labor-inducing is developed and improvised by Researchers from the University of Texas, MD Anderson Cancer Center, in Houston. Contouring is done by examining the medical images of the tumour and accordingly device particular target volumes of rumours and of the surrounding tissues which help to determine the exact amount of radiation to be used. This results in an increased rate of perfection, however, with a considerable scope for human error. If a tumor is located in a very vulnerable place, a little bit of extra radiation would affect the neighboring healthy tissues. If the amount of radiation isn’t sufficient to kill off a tumor and it may continue growing.

Contouring is also an extremely subjective affair, that is it varies from doctor to doctor. The MD Anderson researchers have developed a deep learning process for an objective approach to the tasks of contouring. Their AI-based approach would control the variability by different medical professionals and prevent bias, decreasing the chance of missing the target tumor or over treating normal tissues.

ontours of Radiation Therapy
The researchers used NVIDIA Tesla GPUs on the Maverick supercomputer at the Texas Advanced Computing Center (TACC) and the cuDNN-accelerated Tensorflow deep learning library to analyze data from 52 oropharyngeal cancer patients.

“If we were to do it on our local GPU, it would have taken two months,” said Carlos Cardenas, Ph.D., a researcher working with principal investigator Laurence Court, both at MD Anderson, in an interview with TACC. “But we were able to parallelize the process and do the optimization on each patient by sending those paths to TACC, and that’s where we found a lot of advantages by using the TACC system.”

This algorithm based network to identify and recreate physical contouring pattern is efficient and neutral. This development will be significant in cancer treatment by making radiation therapy for target-specific and efficient and it will reduce uncertainty and damaging healthy tissues. Automating time-consuming processes like contouring and radiation treatment planning could greatly benefit patient care in clinics with low resources, many of which are found in low and middle-income countries because of its cost-effectiveness.

The researchers’ next steps are to translate this process into clinical use, ultimately providing physicians with better information that can lead to improved patient treatments and outcomes.

This is the end that they are aiming at and for that, they’re developing a radiation planning assistant – a fully automated radiation therapy planning tool, which hopefully would launch to partner cancer centers in low-income countries by early next year.

Career

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