Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 13 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
13 measurements spanning 41 days, net +142. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 3,878–4,114 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
17 Sept 2026, 06:40
4,049
+7
13 Sept 2026, 03:36
4,042
-21
9 Sept 2026, 00:00
4,063
-10
3 Sept 2026, 10:03
4,073
-14
31 Aug 2026, 03:09
4,087
+54
27 Aug 2026, 19:46
4,033
+45
24 Aug 2026, 17:11
3,988
+41
20 Aug 2026, 20:53
3,947
+11
18 Aug 2026, 07:11
3,936
+14
14 Aug 2026, 21:54
3,922
+17
11 Aug 2026, 09:28
3,905
-1
8 Aug 2026, 06:15
3,906
-1
7 Aug 2026, 14:32
3,907
first reading
Engagement
17 posts held, back to 8 February 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 17 posts for this entry, the most recent from 29 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
7m 53s
Average length
1m 08s
Measured directly from 7 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
152 reactions across 14 posts, in 13 distinct kinds. The most used accounts for 61.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
94
61.8%
👍
30
19.7%
😍
6
3.95%
🤓
4
2.63%
👀
3
1.97%
🤩
3
1.97%
🥰
3
1.97%
💘
2
1.32%
🤔
2
1.32%
🤗
2
1.32%
❤🔥
1
0.658%
👌
1
0.658%
👏
1
0.658%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 14 of the 17 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 152 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 8 February 2026 to 29 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
10
across the posts below
Posts paid on
10
of 17 we hold a reading for · 59%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @smart_xrayanatomy. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 17 most recent posts we hold for this entry, published 8 February 2026 to 29 July 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🔥Завтра последний день июльской распродажи, и сейчас полный курс по лучевой диагностике доступен со скидкой 50% + летние обновления бесплатно.
🌟 Полный курс ЛУЧЕВОЙ ДИАГНОСТИКИ🌟
✅9 Модулей, включающих введение, общие и частные вопросы лучевой диагностики
🔥Более 300 компьютерных и магнитно-резонансных томограмм с описанием основных патологий
📄 Более 50 интерактивных семинаров
💥Авторские методические материалы, включ…
❓ Что должен уметь делать любой рентгенолог?
✔️Конечно же, определять наличие переломов длинных трубчатых костей!
Часть 1. Общеобразовательная 🙂 поехали)))
📎Итак, подводим итоги опроса: большинство коллег хочет научиться видеть и описывать патологии по снимкам/томограммам.
Что ж, похвально ☺️
Для начала предлагаю посмотреть наш вебинар, который мы записывали для того, чтобы познакомить вас с азами лучевой диагностики.
Понять, с чего мне начать изучение лучевой диагностики62%
Знать, как выглядят органы в лучевом отображении40%
Знать о показаниях к различных методам лучевой диагностики35%
Понимать, что значат те слова, которые пишет врач-рентгенолог в своем протоколе44%
Научиться видеть и описывать патологию по снимкам/томограммам73%
Знать, какие методы лучевой диагностики подходят для исследования определенной системы органов42%
The shares total 296%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
🔤🔤🔤 🔤🔤🔤🔤🔤
Всем привет, ребят 🖐
Давненько не было новых постов от вашего проводника в мир лучевой диагностики. Для начала хочу поделиться с вами, что произошло со мной за последние несколько месяцев 🖥
✔️ Во-первых, 19 июня сдали 3-ий этап ГИА наши ординаторы 2-го года и уже по осени, после сдачи аккредитации, на работу в Московскую область (и не только) придут 16 чудесных врачей-рентгенологов с кафедры лучевой диаг…
❤️🔥Очень красивая реваскуляризирующая операция - формирование экстра-интракраниального микрохирургического анастомоза между поверхностной височной артерией и М4 сегментом левой средней мозговой артерии (анастомоз на фото под стрелкой).
Когда в случае окклюзии внутренней сонной артерии есть возможность улучшить кровоснабжение головного мозга. У данного пациента эффект достигнут 💯
Нейрохирурги - красавчики 😎
❓как сие приспособление будем использовать применительно к МРТ? 🤓
❤8🤔2👀1👌1🤩1
Signed Дарья Смирнова
Showing the 12 most recent of 17 posts we hold for @smart_xrayanatomy. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Polls
The 2 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
Понять, с чего мне начать изучение лучевой диагностики62%
Знать, как выглядят органы в лучевом отображении40%
Знать о показаниях к различных методам лучевой диагностики35%
Понимать, что значат те слова, которые пишет врач-рентгенолог в своем протоколе44%
Научиться видеть и описывать патологию по снимкам/томограммам73%
Знать, какие методы лучевой диагностики подходят для исследования определенной системы органов42%
The shares total 296%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Спамеры оставляют много комментариев, но все не по делу 😆 Тогда создаю опрос: что за патологическое образование в правой доле печени в посте выше?
Киста19%
Аденома11%
Гемангиома53%
Гепатоцеллюлярная карцинома17%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 17 most recent posts we hold, published 8 February 2026 to 29 July 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Psychiatry @psychiatry_vid · 22,942 Telegram ranks this channel #52 of 72 here — alongside 71 others — read 19 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“ExpertЛучевая диагностика” (@smart_xrayanatomy), 4,049 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/smart_xrayanatomy.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.