Live Updates: COVID-19 Cases
  • World 11,980,849
    World
    Confirmed: 11,980,849
    Active: 4,508,285
    Recovered: 6,925,241
    Death: 547,323
  • USA 3,097,538
    USA
    Confirmed: 3,097,538
    Active: 1,608,023
    Recovered: 1,355,524
    Death: 133,991
  • Brazil 1,674,655
    Brazil
    Confirmed: 1,674,655
    Active: 489,865
    Recovered: 1,117,922
    Death: 66,868
  • India 746,506
    India
    Confirmed: 746,506
    Active: 267,204
    Recovered: 458,618
    Death: 20,684
  • Russia 700,792
    Russia
    Confirmed: 700,792
    Active: 217,614
    Recovered: 472,511
    Death: 10,667
  • Peru 309,278
    Peru
    Confirmed: 309,278
    Active: 97,388
    Recovered: 200,938
    Death: 10,952
  • Chile 301,019
    Chile
    Confirmed: 301,019
    Active: 26,340
    Recovered: 268,245
    Death: 6,434
  • Spain 299,210
    Spain
    Confirmed: 299,210
    Active: 270,818
    Recovered: ?
    Death: 28,392
  • UK 286,349
    UK
    Confirmed: 286,349
    Active: 241,958
    Recovered: ?
    Death: 44,391
  • Mexico 268,008
    Mexico
    Confirmed: 268,008
    Active: 72,348
    Recovered: 163,646
    Death: 32,014
  • Iran 248,379
    Iran
    Confirmed: 248,379
    Active: 26,832
    Recovered: 209,463
    Death: 12,084
  • Italy 241,956
    Italy
    Confirmed: 241,956
    Active: 14,242
    Recovered: 192,815
    Death: 34,899
  • Pakistan 237,489
    Pakistan
    Confirmed: 237,489
    Active: 91,602
    Recovered: 140,965
    Death: 4,922
  • Saudi Arabia 217,108
    Saudi Arabia
    Confirmed: 217,108
    Active: 60,252
    Recovered: 154,839
    Death: 2,017
  • South Africa 215,855
    South Africa
    Confirmed: 215,855
    Active: 110,054
    Recovered: 102,299
    Death: 3,502
  • Turkey 207,897
    Turkey
    Confirmed: 207,897
    Active: 17,345
    Recovered: 185,292
    Death: 5,260
  • Germany 198,399
    Germany
    Confirmed: 198,399
    Active: 6,596
    Recovered: 182,700
    Death: 9,103
  • Bangladesh 172,134
    Bangladesh
    Confirmed: 172,134
    Active: 89,099
    Recovered: 80,838
    Death: 2,197
  • France 168,810
    France
    Confirmed: 168,810
    Active: 61,222
    Recovered: 77,655
    Death: 29,933
  • Canada 106,167
    Canada
    Confirmed: 106,167
    Active: 27,573
    Recovered: 69,883
    Death: 8,711
  • China 83,572
    China
    Confirmed: 83,572
    Active: 390
    Recovered: 78,548
    Death: 4,634
  • Netherlands 50,694
    Netherlands
    Confirmed: 50,694
    Active: 44,562
    Recovered: ?
    Death: 6,132
  • S. Korea 13,244
    S. Korea
    Confirmed: 13,244
    Active: 989
    Recovered: 11,970
    Death: 285
  • Australia 8,886
    Australia
    Confirmed: 8,886
    Active: 1,293
    Recovered: 7,487
    Death: 106
  • New Zealand 1,537
    New Zealand
    Confirmed: 1,537
    Active: 23
    Recovered: 1,492
    Death: 22

Deep learning contouring to benefit target-specific Radiation Therapy

Author at TechGenyz Artificial Intelligence
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.
We Are Hiring

Subscribe